{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8fee91a2-2121-44ef-81b3-11ffc68db20d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I read in the Census tract data\n"
     ]
    }
   ],
   "source": [
    "#THIS FILE: Role of \"no-municipality-splits\" in Ohio legislative redistricting complete 11/24\n",
    "#vs OH_legisl_org, we build each HD from starter muni by contiguous munis based on fractional coverage\n",
    "#may need to pull & update code from OH_patch_legisl_org or OH_school_org.  Start from OH_patchAug22\n",
    "\n",
    "from shapely.geometry import Point, LineString, Polygon, box\n",
    "import shapely\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import ast\n",
    "import time\n",
    "from numpy import random\n",
    "from scipy.stats import norm\n",
    "import math\n",
    "tractPopFile = gpd.read_file(\"state_map_files/oh_pl2020_vtd.dbf\")  # ***USING VTDs ***\n",
    "tractPopFile.head()  #about 40 sec to load\n",
    "print(\"I read in the Census tract data\")\n",
    "#handy function for plotting Polygon or multiPolygon tracts and precincts\n",
    "def plotPoly(inputPoly,LW=1):\n",
    "    dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "    if inputPoly.geom_type == dummyPoly.geom_type:\n",
    "        x,y = inputPoly.exterior.xy\n",
    "        plt.plot(x,y,lw=LW)\n",
    "    else:\n",
    "        for geom in inputPoly.geoms:\n",
    "            if geom.area > 0:  #to avoid error with LineString geom parts\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y,lw=LW)  \n",
    "def plotCenter(t,geom,FONTSIZE=10):\n",
    "    plt.text(geom.centroid.x,geom.centroid.y,t,ha='center',fontsize=FONTSIZE)\n",
    "    \n",
    "def r3(number):\n",
    "    result = round(number,3)\n",
    "    return result\n",
    "\n",
    "def r5(number):\n",
    "    result = round(number,5)\n",
    "    return result\n",
    "\n",
    "def getAdjoiners(UNITLIST, UNITNBRS): #returns all units that neighbor a UNITLIST but are not in the UNITLIST \n",
    "    allNbrs = list()\n",
    "    for U in UNITLIST:\n",
    "        allNbrs = allNbrs + UNITNBRS[U]\n",
    "    adjoiners = list( set(allNbrs).difference(set(UNITLIST)) )\n",
    "    return adjoiners\n",
    "\n",
    "def get2nbrs(ULIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    Get the combined list of first- and second-level neighbors of a LIST, using neighborList connectivity.  Excludes the source list\n",
    "    \"\"\"\n",
    "    firstList =  getAdjoiners(ULIST, UNITNBRS)\n",
    "    secondList = getAdjoiners(firstList, UNITNBRS)\n",
    "    twoLevelList = list( set(firstList + secondList).difference(set(ULIST) ) )\n",
    "    return twoLevelList\n",
    "\n",
    "def getContigFromStarter(starter, VLIST, NEIGHBORLIST):  #all contiguous units in VLIST, starting from starter unit\n",
    "    foundList, newList, prevList = [ starter ], [ starter ], [ starter ]\n",
    "    while len(newList) > 0:\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()        \n",
    "    return foundList   \n",
    "\n",
    "def isContiguous(VLIST,NEIGHBORLIST,returnBiggestPiece=False):\n",
    "    \"\"\"\n",
    "    This method determines if all items in a list form a continuous chain of neighbors based on the passed neighborlist\n",
    "    Empty lists are considered contiguous.  If discontiguous, a less-than-majority piece list is returned,\n",
    "     unless giveBig=True, in which case we return the biggest piece\n",
    "    \"\"\"    \n",
    "    isUnbroken, newList, foundList = True, list(), list()\n",
    "    if len(VLIST) > 0:\n",
    "        foundList, newList, prevList = [ VLIST[0] ], [ VLIST[0] ], [ VLIST[0] ]\n",
    "    while len(newList) > 0:  #this round's list of neighbors\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()      \n",
    "    pickedPieceList = foundList.copy()  #default contiguous sublist to pass back to main\n",
    "    \n",
    "    if len(foundList) < len(VLIST):  #not contiguous\n",
    "        isUnbroken  = False\n",
    "        pieceLists, remainingList = [foundList], list( set(VLIST).difference(set(foundList) ) )\n",
    "        if returnBiggestPiece == True:  #we were asked for the biggest piece, not a random small one, so we must find them all\n",
    "            if len(foundList) < 0.5*len(VLIST):\n",
    "                while len(remainingList) > 0:\n",
    "                    newList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                    pieceLists.append(newList)\n",
    "                    remainingList = list(set(remainingList).difference(set(newList)))\n",
    "                pieceLengths = [len(pL) for pL in pieceLists]\n",
    "                pickedPieceList = pieceLists[ pieceLengths.index(np.max(pieceLengths)) ]\n",
    "            \n",
    "        else: #quickly return a contiguous sub-list that's at most half the total units in the list\n",
    "            if len(foundList) > 0.5*len(VLIST): #pick a different piece; this one is the majority\n",
    "                pickedPieceList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                \n",
    "    return isUnbroken, pickedPieceList\n",
    "\n",
    "def enclaveCheck(UNITLIST,UNITNBRS,maxLoops=2):  #TRY 2 FOR OHIO V2.  USUALLY 4\n",
    "    \"\"\"\n",
    "    This method determines if a list of units has an unbroken boundary AND whether its complement has an unbroken boundary\n",
    "    If the complement boundary is broken, there is an enclave or the district is so disconnected its adjoining units aren't contiguous\n",
    "    The method returns contiguity of boundary and of its adjoiners.  Also returns the lists of boundary and complement-boundary units\n",
    "      If either of these is broken, only a contiguous sublist is returned that is guaranteed to be smaller than half (for finding enclaves)\n",
    "      maxLoops is the number of loops for expanding neighbors-of-neighbors for contiguity of the units outside the passed unit-list\n",
    "    \"\"\"\n",
    "    UNITSET = set(UNITLIST)\n",
    "    ADJLIST =  get2nbrs(UNITLIST, UNITNBRS)  #in case direct adjoiners are only queen-adjacent\n",
    "    #adjoinersOfAdjoiners = getAdjoiners(ADJLIST,  UNITNBRS)\n",
    "    #BDRYLIST = list( set(UNITLIST).intersection(set(adjoinersOfAdjoiners)) )  #this might fail for queen-adjacent boundary units\n",
    "    BDRYLIST = list (set(get2nbrs(ADJLIST,UNITNBRS)).intersection(UNITSET) )  #in case inHD boundary is only queen-adjacent\n",
    "    noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)  \n",
    "    unbroken, smallPieceList = isContiguous(BDRYLIST, UNITNBRS)\n",
    "    if not unbroken: #could be that district's boundary intersects the state boundary or there is a nonHD enclave inside the HD\n",
    "        unbroken, smallPieceList = isContiguous(UNITLIST, UNITNBRS)  #slower check for full district, not just its boundary \n",
    "    nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "    while nLoops <= maxLoops and not noEnclave:\n",
    "        nLoops +=1\n",
    "        newSet = set(ADJLIST)\n",
    "        for UU in ADJLIST:\n",
    "            newSet = newSet.union( set(UNITNBRS[UU]).difference(UNITSET) )\n",
    "        ADJLIST = list(newSet)\n",
    "        noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)\n",
    "    #isJiggy = noEnclave and unbroken\n",
    "    return unbroken, noEnclave, smallPieceList, enclaveList\n",
    "\n",
    "def getBdryNonEdgers(UNITLIST, UNITNBRS): #all in-district boundary units that neighbor a non-district unit\n",
    "    ALLnonHDnbrs = set()\n",
    "    for UUU in UNITLIST:\n",
    "        ALLnonHDnbrs = ALLnonHDnbrs.union(set(UNITNBRS[UUU])).difference(set(UNITLIST))\n",
    "    BdryNonEdgerSet = set()\n",
    "    for UUU in UNITLIST:\n",
    "        if len(set(UNITNBRS[UUU]).intersection(ALLnonHDnbrs)) > 0:\n",
    "            BdryNonEdgerSet.add(UUU)\n",
    "    return list(BdryNonEdgerSet)\n",
    "\n",
    "def getEnclaveLists(UNITLIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    finds ALL units enclaved by a UNITLIST, parsed into lists of contiguous pieces\n",
    "    We assume the largest contiguous complement to the UNITLIST is not an enclave, but rather the majority of the HD complement\n",
    "    if the UNITLIST's complement (all couldBeEnclaved) is contiguous, the returned list will be blank\n",
    "    \"\"\"\n",
    "    eSets, nU = list(), len(UNITNBRS)\n",
    "    offmapList = list()\n",
    "    for i,L in enumerate(UNITNBRS):\n",
    "        if len(L) == 0:\n",
    "            offmapList.append(i)  #offmap list are units with no neighbors (were surrounded)\n",
    "    complementSet = set([i for i in range(nU)] ).difference( set(UNITLIST + offmapList) )    \n",
    "    remaining2nbrs = get2nbrs(UNITLIST, UNITNBRS)\n",
    "    \n",
    "    isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS) #quicker than contig check on entire complement\n",
    "    while not isContig:  #this will kick out before writing the final sublist = map majority\n",
    "        starter = shortList[0]\n",
    "        newEnclaveList = getContigFromStarter(starter, list(complementSet), UNITNBRS)\n",
    "        eSets.append(set(newEnclaveList))\n",
    "        remaining2nbrs = list(set(remaining2nbrs).difference(set(shortList)) )\n",
    "        isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS)\n",
    "        \n",
    "        # couldBeEnclaved = list( set(couldBeEnclaved).difference(set(newEnclaveList)) )  #revised 18-Feb-24 -- was slower\n",
    "    fused_eSets = set()\n",
    "    for i, eSet in enumerate(eSets):\n",
    "        fused_eSets = fused_eSets.union(eSet)\n",
    "        for j in range(i+1, len(eSets) ) :\n",
    "            eSets[j] = eSets[j].difference(eSet)  #in case contiguity occurs, but not in 2-neighbor list; avoid double-count\n",
    "    remnant_eSet = complementSet.difference(fused_eSets) \n",
    "    eLengths = [len(eSet) for eSet in eSets]\n",
    "    if len(eSets) > 0:\n",
    "        if len(remnant_eSet) < np.max(eLengths):  #exchange the small remnant for the biggest found \"enclave\" (usually the major complement) \n",
    "            eSets[eLengths.index(np.max(eLengths))] = remnant_eSet.copy()\n",
    "    eLists = [list(eSet) for eSet in eSets]\n",
    "    return eLists\n",
    "\n",
    "def wontEnclave(proposedU, dList, NBRLIST, mapBDRYLIST):  #TRY MAXLOOPS = 3 FOR OH REDO, NOT USUAL 6\n",
    "    \"\"\"\n",
    "    This method checks if adding a proposedU to a dList (list of units in a district) will create an \"enclave\" of units in the dList's complement\n",
    "    via two problems:  A) the dList will now have a discontiguous set of units on the map boundary.  The full map boundary list is mapBDRYLIST\n",
    "      B) The non-dList neighbors of dList units aren't contiguous\n",
    "    The method doesn't require that the dList wontEnclave without the proposedU included; it just checks the proposedU + dList combination\n",
    "    It also doesn't check that the dList is itself contiguous with or without proposedU\n",
    "    In that sense, it is more limited than enclaveCheck\n",
    "    \"\"\"\n",
    "    wontEnclave = True\n",
    "    newList, newSet = dList + [proposedU], set(dList + [proposedU])\n",
    "    unitsOnBoundary = list( set(mapBDRYLIST).intersection(newSet) )\n",
    "    wontEnclave, __ = isContiguous(unitsOnBoundary,NBRLIST)  #first check - does district touch MAP boundary in multiple places? (quick FAIL)\n",
    "    if wontEnclave: #slower check below for internal enclaves\n",
    "        adjoiners = get2nbrs(newList, NBRLIST)  #2-level to protect for queen adjacency in boundary        \n",
    "        wontEnclave, __ = isContiguous(adjoiners,NBRLIST)\n",
    "        if not wontEnclave:\n",
    "            nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "            maxLoops, ADJLIST = 3, adjoiners #unlike enclaveCheck, here we just arbitrarily set a number of loops for search expansion\n",
    "            while nLoops <= maxLoops and not wontEnclave:\n",
    "                nLoops +=1\n",
    "                adjSet = set(ADJLIST)  #align nomenclature w enclaveCheck\n",
    "                for UU in ADJLIST:\n",
    "                    adjSet = adjSet.union( set(NBRLIST[UU]).difference(set(newList)) )\n",
    "                ADJLIST = list(adjSet)\n",
    "                wontEnclave, __ =   isContiguous(ADJLIST, NBRLIST)\n",
    "        \n",
    "    return wontEnclave\n",
    "\n",
    "def isRookAdj(geo1, geo2):  #intersection with rook (not queen) adjacency\n",
    "    isRookAdj = False\n",
    "    if geo1.intersects(geo2):\n",
    "        if (geo1.intersection(geo2)).geom_type != Point(0,0).geom_type:\n",
    "            isRookAdj = True\n",
    "    return isRookAdj\n",
    "\n",
    "def getWeightedAvgAndSD(LIST, WEIGHTS):\n",
    "    nWeights = len(WEIGHTS)\n",
    "    normWeights = [WEIGHTS[i] / np.sum(WEIGHTS) for i in range(nWeights) ]\n",
    "    AVG = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        AVG += normWeights[i] * value\n",
    "    sumVar = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        sumVar += normWeights[i] * (value - AVG)**2\n",
    "    SD = sumVar ** 0.5     #don't need to normalize again since weights were normalized\n",
    "    return AVG, SD\n",
    "\n",
    "def getHDcp(TRACTCP,TRACTPOP, TRACTLIST, SPLITTRACTNO = -777,SPLITTRACTUSE = 1.):  #population centerpoint of a Home District or county (cluster)\n",
    "    cpx, cpy, sumPop = 0.,0., 0.\n",
    "    for tt in TRACTLIST:\n",
    "        USE = 1.\n",
    "        if tt ==    SPLITTRACTNO:\n",
    "            USE =   SPLITTRACTUSE\n",
    "        sumPop += USE*TRACTPOP[tt]\n",
    "        cpx +=    USE*TRACTPOP[tt] * TRACTCP[tt].x\n",
    "        cpy +=    USE*TRACTPOP[tt] * TRACTCP[tt].y\n",
    "    HDCP_ = Point(cpx/sumPop, cpy/sumPop)\n",
    "    return HDCP_\n",
    "\n",
    "dummyPoly = Polygon([(0,0),(0,1),(1,1)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a9e2fbed-247e-4a00-be18-5507b7e2b88f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 8941 popn tracts for OH\n"
     ]
    }
   ],
   "source": [
    "# EXTRACT TRACT GEOMETRIES AND POPULATIONS INTO LISTS, COMPUTE TRACT AREAS\n",
    "STATE = \"OH\"\n",
    "tractGeom = tractPopFile['geometry']  #for some states, replace with tractGeomFile\n",
    "tractPop = tractPopFile['P0010001']\n",
    "tractVAP = tractPopFile['P0030001']   #NEW 3/2/22 - USE VAP\n",
    "# tractPop2 = tractPopFile['P0020001']   #not needed; confirmed that this matches P00100001 exactly\n",
    "tractHisp = tractPopFile['P0040002']   #NEW 3/2/22 - USE VAP\n",
    "tractBlack = tractPopFile['P0030004']  #NEW 3/2/22 - USE VAP\n",
    "tractCountyNo = tractPopFile['COUNTYFP20']\n",
    "nTracts = len(tractPop)\n",
    "nVTDs = nTracts #nomenclature\n",
    "print(\"there are {0} popn tracts for {1}\".format(nTracts, STATE) )\n",
    "tractArea = [0.]*nTracts\n",
    "tractCountyNo = tractCountyNo.to_numpy()\n",
    "countyNo = [0]*nTracts\n",
    "for t in range (0,nTracts) :  #from odd-numbered counties in US Census list to integer list\n",
    "    tractArea[t] = tractGeom[t].area\n",
    "    countyNo[t] = int((int(tractCountyNo[t]) - 1)/2)\n",
    "isSkippedTract = [0] *nTracts  #this will house a temporary list of tracts for manipulation\n",
    "tractPop = tractPop.to_numpy()  #to avoid panda overwrite grousing\n",
    "tractBlack= tractBlack.to_numpy()\n",
    "tractHisp = tractHisp.to_numpy()\n",
    "tractVAP = tractVAP.to_numpy()\n",
    "stateVAP = np.sum(tractVAP)\n",
    "nCounties = int( np.max(countyNo)+1)\n",
    "skipList = [8197, 4634, 3730, 4458, 840, 2974, 1008]\n",
    "for t in skipList : #coastal vtds for Ohio already known\n",
    "    isSkippedTract[t] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a619e262-3e70-4945-87b1-58245cc514c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on tract 0\n",
      "working on tract 1000\n",
      "working on tract 2000\n",
      "working on tract 3000\n",
      "working on tract 4000\n",
      "working on tract 5000\n",
      "working on tract 6000\n",
      "working on tract 7000\n",
      "working on tract 8000\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CREATE COUNTY-LEVEL MAP OF THIS STATE - excluding lakeshore tracts from county building\n",
    "for s in skipList :\n",
    "    countyNo[s] = -999  #don't count these lakeshore tracts as part of a county\n",
    "dummyPoly = Polygon([ (0,0),(1,0),(1,1)])\n",
    "countyGeom = [dummyPoly]*nCounties\n",
    "lakeErieGeom = []\n",
    "countyPop = [0.]*nCounties\n",
    "nCountyTracts = [0]*nCounties  #how many tracts found in this county\n",
    "countyTractList = [list() for c in range(nCounties) ]\n",
    "for t in range(nTracts):  #now loop through tracts, assign each to county, build county polygons\n",
    "    if t%1000 == 0:\n",
    "        print(\"working on tract\",t)\n",
    "    if t not in skipList:\n",
    "        c = int(countyNo[t])\n",
    "        countyTractList[c].append(t)\n",
    "        nCountyTracts[c] +=1   #found another tract that belongs to this county\n",
    "        countyPop[c] += tractPop[t]\n",
    "        if nCountyTracts[c] == 1:  #this is the first tract found for this county\n",
    "            countyGeom[c] = tractGeom[t]  #seed the county geometry polygon\n",
    "        else:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "countyMAP = countyGeom[0]\n",
    "for c in range(nCounties):  #now build the state map from the counties\n",
    "    plotPoly(countyGeom[c])\n",
    "    plotCenter(c,countyGeom[c],8)\n",
    "    countyMAP = countyMAP.union(countyGeom[c])\n",
    "plotPoly(countyMAP)\n",
    "plt.show()   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cda12941-0eef-4a29-a376-dd0d4bc2927b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "99 districts, each with avgDistrictPop of 119186.343\n",
      "I will now build a map from the counties and display the whole county districts\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are a total of 7 small or perfect counties that we will keep whole in Home Districts\n"
     ]
    }
   ],
   "source": [
    "#quick block to flag the whole county-districts -- though we do not use any whole-county units in this version\n",
    "MAP = dummyPoly\n",
    "perfectCounty = [0]*nCounties  #\"perfect\" counties have the perfect population for a whole district\n",
    "wholeCounty = [0]*nCounties    #\"whole\" counties are either perfect or small enough that they should be kept whole\n",
    "minCountyRatio = 0.15   #small counties will naturally be unsplit.  We'll set a reasonable arbitrary threshold.\n",
    "lockedTract = [0]*nTracts\n",
    "nDistricts = 99 #Ohio statehouse\n",
    "statePop = np.sum(tractPop)\n",
    "avgDistrictPop = statePop/nDistricts\n",
    "aDP = avgDistrictPop\n",
    "maxDevn = 0.05\n",
    "print(nDistricts,\"districts, each with avgDistrictPop of\",r3(avgDistrictPop))\n",
    "print(\"I will now build a map from the counties and display the whole county districts\")\n",
    "for c in range(nCounties):\n",
    "    if MAP == dummyPoly:\n",
    "        MAP = countyGeom[c]\n",
    "    else:\n",
    "        MAP = MAP.union(countyGeom[c])\n",
    "    if countyPop[c] >= (1.-maxDevn)*avgDistrictPop and countyPop[c] <= (1.+maxDevn)*avgDistrictPop :\n",
    "        perfectCounty[c] = 1\n",
    "        wholeCounty[c] = 1\n",
    "        plotPoly(countyGeom[c])\n",
    "    if countyPop[c] < minCountyRatio*avgDistrictPop:  #small counties will naturally be unsplit.\n",
    "        wholeCounty[c] = 1\n",
    "plotPoly(MAP)\n",
    "plt.show()\n",
    "print(\"there are a total of\",np.sum(wholeCounty),\"small or perfect counties that we will keep whole in Home Districts\")\n",
    "for t in range(nTracts):\n",
    "    if isSkippedTract == 0:\n",
    "        if wholeCounty[countyNo[t]] == 1:  #this tract is part of a whole county per Article XI.3.c.2\n",
    "            lockedTract[t] = 1             # ... or in a county that is so small we are keeping that county whole"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cccb8f16-3c9b-4fc8-9f93-79dc8cbebedc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets import the vtd - unit topology \n"
     ]
    }
   ],
   "source": [
    "print(\"Lets import the vtd - unit topology \")\n",
    "infile = \"./state_map_files/OH99muni-unitTopologies_03Nov24.csv\"\n",
    "topologyDF = pd.read_csv(infile)\n",
    "muniPop = topologyDF[\"unitPop\"]\n",
    "nListString = topologyDF[\"unitNbrs\"]\n",
    "muniVTDlistString = topologyDF[\"unitVTDlist\"]\n",
    "muniCountyNo = topologyDF[\"unitCountyNo\"]\n",
    "muniCPx = topologyDF[\"centroid x\"]\n",
    "muniCPy = topologyDF[\"centroid y\"]\n",
    "nMunis = len(muniPop)\n",
    "muniNbrs = [ast.literal_eval(nListString[m]) for m in range(nMunis)]\n",
    "muniVTDlist = [ast.literal_eval(muniVTDlistString[m]) for m in range(nMunis)]\n",
    "borderUnits = list()\n",
    "onBorder = topologyDF[\"onBorder\"]\n",
    "for m in range(nMunis):\n",
    "    if onBorder[m] == 1:\n",
    "        borderUnits.append(m)\n",
    "countyUnitList = [list() for c in range(nCounties)]\n",
    "for m in range(nMunis):\n",
    "    countyUnitList[muniCountyNo[m]].append(m)"
   ]
  },
  {
   "cell_type": "raw",
   "id": "0b53ad0b-1d81-478c-81ad-dd20b74163d5",
   "metadata": {},
   "source": [
    "print(\"BELOW IS NOT YET TESTED.  FOR NOW, DON'T FUSE SMALL COUNTIES - NOT IN OHIO RULES ANYWAY\")\n",
    "print(\"now create units, which are usually whole munis, but we will fuse munis in small counties.\")\n",
    "print(\"The OH_defineMunisSimplified code already split out our big Munis\")\n",
    "print(\"in muniSnap code, we will NOT IMPLEMENT perfect counties.  (In Muni-County, we will fuse perfect counties as well.)\")\n",
    "oldCountyMuniSet = [set() for c in range(nCounties)]\n",
    "willBeFused = [0]*nMunis\n",
    "for m in range(nMunis):\n",
    "    oldCountyMuniSet[muniCountyNo[m]].add(m)\n",
    "smallCounties = list()\n",
    "fusedCountyOldNbrLists = list()\n",
    "newUnitVTDlist = list()  #essentially, we add whole counties to the end of the muni list, then transfer all neighbors ...\n",
    "fusedCountyOldMuniNo = [-999]*nCounties\n",
    "counter = nMunis\n",
    "for c in range(nCounties):\n",
    "    if wholeCounty[c] == 1 and perfectCounty[c] != 1:\n",
    "        fusedCountyOldMuniNo[c] = counter\n",
    "        counter +=1\n",
    "        smallCounties.append(c)\n",
    "        newNbrList = list()\n",
    "        newVTDset = set(muniVTDlist[ oldCountyMuniSet[c][0] ])\n",
    "        for m in oldCountyMuniSet[c] :\n",
    "            willBeFused[m] = 1\n",
    "            newNbrList.append(muniNbrs[m])\n",
    "            newVTDset = newVTDset.union(set(muniVTDlist[m]))\n",
    "        fusedCountyOldNbrLists.append( list(set(newNbrList).difference(oldCountyMuniSet[c]) ) )\n",
    "        newUnitVTDlist.append(list(newVTDset))\n",
    "oldNbrSets = list()\n",
    "for m in range(nMunis):\n",
    "    if willBeFused[m] == 1:\n",
    "        oldNbrSets.append(set())\n",
    "    else:\n",
    "        oldNbrSets[m] = set()\n",
    "        for mm in muniNbrs[m]:\n",
    "            if willbeFused[mm] == 1:\n",
    "                oldNbrSets[m].add(fusedCountyOldMuniNo[muniCountyNo[mm])\n",
    "            else:\n",
    "                oldNbrSets[m].add(mm)\n",
    "\n",
    "newUnitNo, counter = [-999]*nMunis, 0  #pointer to new unit no for current list of munis (even fused ones) + fused counties\n",
    "for m in range(nMunis):\n",
    "    if willBeFused[m] == 0:\n",
    "        newUnitNo[m] = counter\n",
    "        counter +=1\n",
    "for c in smallCounties:\n",
    "    newUnitNo.append(counter)  #by convention, newly fused counties were put at end of list of munis\n",
    "    counter +=1\n",
    "#then we update unit nbr numbers\n",
    "nNewUnits = counter\n",
    "unitNbrs, unitCP, unitPop = [list() for u in range(nNewUnits)], [list() for u in range(nNewUnits)], [list() for u in range(nNewUnits)]\n",
    "for m in range(nMunis):\n",
    "    if willBeFused[m] == 0:\n",
    "        u = newUnitNo[m]\n",
    "        unitPop[u] = muniPop[m]\n",
    "        unitCP[u] = muniCP[m]\n",
    "        for mm in oldNbrSets[m]:\n",
    "            unitNbrs[u].append(newUnitNo[mm])\n",
    "counter = nMunis\n",
    "for c in range(nCounties):\n",
    "    if c in smallCounties:\n",
    "        u = counter\n",
    "        unitPop[u] = countyPop[c]\n",
    "        unitCP[u] = countyGeom[c].centroid\n",
    "        for mm in oldNbrSets[fusedCountyOldMuniNo[c]]:\n",
    "            unitNbrs[u].append(newUnitNo[mm[)\n",
    "        counter +=1\n",
    "\n",
    "\n",
    "for m in range(nMunis, nMunis + len(smallCounties) ) :\n",
    "\n",
    "unitGeom,unitCP, unitList,unitCountyNo = list(),list(),list()\n",
    "for m in range(nMunis):\n",
    "    if muniCountyNo[m] in smallCounties:\n",
    "        \n",
    "for c in smallCounties:\n",
    "    for m in range(nMunis):\n",
    "        \n",
    "\n",
    "countyMuniList = [list() for c in range(nCounties)] #building the list of original munis per county\n",
    "maxMuniPop = 1.05 * aDP\n",
    "for m in range(nMunis):\n",
    "    countyMuniList[muniCountyNo[m]].append(m)\n",
    "isFusedMuni = [0]*nMunis\n",
    "for c in range(nCounties):\n",
    "    if wholeCounty[c] == 1 and not perfectCounty[c] == 1:\n",
    "        for m in countyMuniList[c]:\n",
    "            isFusedMuni[m] = 1\n",
    "oldMuniList, newMuniNo, oldNbrList,nUnits, unitPop = list(), [-999]*nMunis, list(), 0, list()\n",
    "unitCountyNo,unitCPx, unitCPy = list(),list(), list()\n",
    "countyUnitList = [list() for c in range(nCounties)]\n",
    "for m in range(nMunis):\n",
    "    if isFusedMuni[m] == 0:\n",
    "        oldMuniList.append([m])\n",
    "        oldNbrList.append(muniNbrs[m])\n",
    "        unitPop.append(muniPop[m])\n",
    "        newMuniNo[m] = nUnits\n",
    "        countyUnitList[muniCountyNo[m]].append(nUnits)\n",
    "        unitCountyNo.append(muniCountyNo[m])\n",
    "        unitCPx.append(muniCPx[m])\n",
    "        unitCPy.append(muniCPy[m])\n",
    "        nUnits +=1\n",
    "for c in range(nCounties):  #now append the fused counties as new 'munis'\n",
    "    if wholeCounty[c] == 1 and not perfectCounty[c] == 1: \n",
    "        countyUnitList[c].append(nUnits)\n",
    "        unitCountyNo.append(c)\n",
    "        unitCPx.append(countyGeom[c].centroid.x)\n",
    "        unitCPy.append(countyGeom[c].centroid.y)\n",
    "        nUnits +=1\n",
    "        oldMuniList.append(countyMuniList[c])\n",
    "        nSet =  set()      \n",
    "        for m in countyMuniList[c]:\n",
    "            nSet = nSet.union(set(muniNbrs[m]))\n",
    "            newMuniNo[m] = nUnits #all these county's munis will be in this new unit\n",
    "        nSet = nSet.difference(set(countyMuniList[c]))\n",
    "        oldNbrList.append(list(nSet))  #this is the list of munis (old numbering) that neighbor this fused county-muni\n",
    "        unitPop.append(np.sum([muniPop[m] for m in countyMuniList[c] ] ) )\n",
    "\n",
    "unitNbrs = list()\n",
    "for u in range(nUnits):\n",
    "    nSet = set()\n",
    "    if len(oldMuniList[u]) == 1:  #this was and is a single muni.  Might be a straighter way to do this, but it works ...\n",
    "        m = oldMuniList[u][0]\n",
    "        for mm in muniNbrs[m]: \n",
    "            nSet.add(newMuniNo[mm])  #this works even if muni was fused into a county\n",
    "    else:  # a newly fused county of munis\n",
    "        for mm in oldNbrList[u]:\n",
    "            nSet.add(newMuniNo[mm])\n",
    "    unitNbrs.append(list(nSet))\n",
    "              \n",
    "print(\"Here are the number of munis by county\")\n",
    "plt.scatter([c for c in range(nCounties)],[len(countyUnitList[c]) for c in range(nCounties)])\n",
    "plt.show()\n",
    "\n",
    "##################### COME BACK TO THIS.  NOT SURE HOW TO MANAGE VTD FRAGS HERE *******"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7cba3f2e-dacb-443d-b639-acac0bd219a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If we are not fusing in small counties, simply copy over from munis to units\n",
      "building VTD-based geom for muni / unit 0\n",
      "building VTD-based geom for muni / unit 500\n",
      "building VTD-based geom for muni / unit 1000\n",
      "building VTD-based geom for muni / unit 1500\n",
      "building VTD-based geom for muni / unit 2000\n",
      "building VTD-based geom for muni / unit 2500\n",
      "building VTD-based geom for muni / unit 3000\n"
     ]
    }
   ],
   "source": [
    "print(\"If we are not fusing in small counties, simply copy over from munis to units\")\n",
    "unitPop, unitCountyNo, unitCPx, unitCPy = muniPop.copy(), muniCountyNo.copy(), muniCPx.copy(), muniCPy.copy()\n",
    "nUnits, unitVTDlist = len(unitPop),[muniVTDlist.copy() for m in range(nMunis)]\n",
    "unitCP =      [Point(unitCPx[u],unitCPy[u]) for u in range(nUnits)]\n",
    "unitVTDlist = [muniVTDlist[u].copy() for u in range(nUnits)]\n",
    "unitNbrs =    [muniNbrs[u].copy() for u in range(nUnits)]\n",
    "unitGeom = [tractGeom[unitVTDlist[u][0]] for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if u % 500 == 0:\n",
    "        print(\"building VTD-based geom for muni / unit\",u)\n",
    "    for v in unitVTDlist[u]:\n",
    "        unitGeom[u] = unitGeom[u].union(tractGeom[v])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e0545c19-3336-4bad-9acf-5eb90106ff6c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here are the unsplittable municipalities, between 50pct and 105% of a district\n",
      "23 81146.0 17\n",
      "38 72246.0 75\n",
      "302 65211.0 46\n",
      "374 60068.0 49\n",
      "378 63399.0 8\n",
      "958 63750.0 8\n",
      "and which ones are 0.4 - 0.5 aDP?\n",
      "    36 58644.0 11\n",
      "    204 51114.0 76\n",
      "    260 49692.0 17\n",
      "    266 50942.0 17\n",
      "    301 52656.0 46\n",
      "    332 49934.0 44\n",
      "    365 57123.0 56\n"
     ]
    }
   ],
   "source": [
    "unsplittableUnits = list()\n",
    "print(\"Here are the unsplittable municipalities, between 50pct and 105% of a district\")\n",
    "for u in range(nUnits):\n",
    "    if unitPop[u] < 1.05*avgDistrictPop and unitPop[u] > 0.5 * avgDistrictPop:\n",
    "        unsplittableUnits.append(u)\n",
    "        print(u, r3(unitPop[u]),unitCountyNo[u])\n",
    "print(\"and which ones are 0.4 - 0.5 aDP?\")\n",
    "for u in range(nUnits):\n",
    "    if unitPop[u] < 0.5*avgDistrictPop and unitPop[u] > 0.4 * avgDistrictPop:\n",
    "        print(\"   \",u, r3(unitPop[u]),unitCountyNo[u])"
   ]
  },
  {
   "cell_type": "raw",
   "id": "fe6b3dde-10af-4e01-ab58-49df834d85bf",
   "metadata": {},
   "source": [
    "Big Ohio cities list, and their 2020 Census pops:\n",
    "Akron - 190,469.   Enforce 0% or 60%+.  My calcn nearly on target\n",
    "Cincy - 309,317. Enforce 0% or 80%+   My calcn nearly on-target.\n",
    "Cleveland - 372,624 = 3 whole districts.  I count 417,000 which likely includes crannies. --> sprawling, enforce > 0.2\n",
    "Columbus - ~800,000 in Franklin County - seven whole districts but sprawling.  10 or 11 reasonable, no restrictions\n",
    "Dayton - 137,644.  Enforce 0% or 20%+  My calcn nearly on target\n",
    "Toledo - 270,871. No restriction.   My calcn nearly on target\n",
    "--------\n",
    "Parma 81,146 -- I AM OVERCOUNTING, but ok to keep whole  (note, these are from old by-precinct-name method)\n",
    "Canton 70,872 -- I AM OVERCOUNTING, but ok to keep whole\n",
    "Youngstown 67,296 -- I am undercounting (60,059)\n",
    "Lorain 63,468  -- about right\n",
    "Hamilton 61,932  -- about right\n",
    "Green 60,424 - about right  #Census has several CDP's inside Green\n",
    "West 8 = West Chester 64,901 -- about right\n",
    "not Springfield 57,719\n",
    "not Fairfield 42,000 -- we split out Fairfield township :-)\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "78564573-ce6d-4d0e-b2d4-3c33f25b0be6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pull in the any-split Home Districts ...\n",
      "Now convert (approximately) to full VTD lists. We didn't store the VTDfrag lists, so use binary in-out if frac > 0.5\n",
      "Lets compare our true HDpops to this partial-based calculation\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#10/27/24\n",
    "print(\"Pull in the any-split Home Districts ...\")\n",
    "infile = \"./2024state_HD_output/OH8941legisl60_1p5PatchedVTDs.csv\"\n",
    "HDdf = pd.read_csv(infile)\n",
    "HDvtdListString, partialString, fracString = HDdf[\"HDvtdList\"], HDdf[\"partials\"],HDdf[\"HDvtdFrac\"]\n",
    "HDCPx, HDCPy, HDwt = HDdf[\"centroid x\"],HDdf[\"centroid y\"], HDdf[\"HDweight\"]\n",
    "HDvTruePop = HDdf[\"HDvPop\"]\n",
    "HDCP = [Point(HDCPx[v], HDCPy[v]) for v in range(nVTDs)]\n",
    "hdCP = HDCP.copy() #nomenclature\n",
    "nHDs = len(HDvtdListString)\n",
    "HDvtdList = [ast.literal_eval(HDvtdListString[h]) for h in range(nHDs)]\n",
    "HDpartials = [ast.literal_eval(partialString[h]) for h in range(nHDs)]\n",
    "HDvtdFrac = [ast.literal_eval(fracString[h]) for h in range(nHDs)]\n",
    "print(\"Now convert (approximately) to full VTD lists. We didn't store the VTDfrag lists, so use binary in-out if frac > 0.5\")\n",
    "for h in range(nHDs):\n",
    "    for i, frac in enumerate(HDvtdFrac[h]):\n",
    "        if frac >= 0.5:\n",
    "            HDvtdList[h].append(HDpartials[h][i])\n",
    "print(\"Lets compare our true HDpops to this partial-based calculation\")\n",
    "HDvtdPop = [np.sum ([ tractPop[v] for v in HDvtdList[h] ] ) for h in range(nHDs) ]\n",
    "popRatio = [(HDvtdPop[h] + 0.0001) / (HDvTruePop[h] + 0.0001) for h in range(nHDs) ]\n",
    "plt.scatter([h for h in range(nHDs)], popRatio, label=\"converted to true pop\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "#HDvtdFracList  = [list() for h in range(nHDs)]  ##modified 11/24 - do not use VTD fragments\n",
    "#for h in range(nHDs):\n",
    "#    for v in HDvtdList[h]:\n",
    "#        for f in VTDchildren[v]:\n",
    "#            HDvtdFracList[h].append(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1fbef9d8-35f8-49cf-bb3e-6d6acf517033",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8941 119186.34343434343\n",
      "3.0\n"
     ]
    }
   ],
   "source": [
    "print(nHDs, aDP)\n",
    "print(np.min(unitPop))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9fe8940f-434d-405d-b52f-e17074715fcf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now snap each HD to units.  Each HD is assigned its home muni, then we build out whole munis, then ...\n",
      "... we add munis that were partially included, biasing toward close, mostly full ones\n",
      "working on snapping HD 195 in unit 0 to whole munis\n",
      "working on snapping HD 4131 in unit 269 to whole munis\n",
      "working on snapping HD 395 in unit 572 to whole munis\n",
      "HD 2331  has only 0.008 pop/aDP. We will swell by nearest munis to shore it up\n",
      "HD 1006  has only 0.038 pop/aDP. We will swell by nearest munis to shore it up\n",
      "working on snapping HD 2604 in unit 1379 to whole munis\n",
      "working on snapping HD 4309 in unit 2572 to whole munis\n"
     ]
    }
   ],
   "source": [
    "#10/27/24\n",
    "print(\"Now snap each HD to units.  Each HD is assigned its home muni, then we build out whole munis, then ...\")\n",
    "print(\"... we add munis that were partially included, biasing toward close, mostly full ones\")\n",
    "minSnapFrac, minEligFrac = 0.667, 0.1 #we auto-add contig munis at least this full in HDvtdList\n",
    "homeU, HDvPop, HDunitList = [-888]*nHDs, [0.]*nHDs, [list() for h in range(nHDs) ]\n",
    "popHDlist = list()\n",
    "for u in range(nUnits):\n",
    "    origArea = np.sum( [tractArea[v] for v in unitVTDlist[u] ] )\n",
    "    origL = origArea ** 0.5  #characteristic local district diameter\n",
    "    for v in unitVTDlist[u]:\n",
    "        homeU[v] = u\n",
    "        popHDlist.append(v)\n",
    "for nh,h in enumerate(popHDlist):\n",
    "    if nh%2000 == 0:\n",
    "        print(\"working on snapping HD\",h,\"in unit\",homeU[h],\"to whole munis\")\n",
    "    currPop, addedUset = unitPop[homeU[h]], { homeU[h] }\n",
    "    useFrac = [0.]*nUnits\n",
    "    for v in HDvtdList[h]:\n",
    "        useFrac[homeU[v]] += tractPop[v] / unitPop[homeU[v]]\n",
    "    shouldAddUset, hasFracUset = set(), set()\n",
    "    for u in range(nUnits):\n",
    "        if useFrac[u] > minSnapFrac :  #munis more than 2/3 captured should be snapped if contig path found\n",
    "            shouldAddUset.add(u)\n",
    "        if useFrac[u] > minEligFrac :  #munis that were at least 10% captured are eligible to be snapped\n",
    "            hasFracUset.add(u)\n",
    "    shouldAddUset = shouldAddUset.difference(addedUset)  #at this point, this knocks out just the home muni\n",
    "    nJustAdded = 1\n",
    "    while nJustAdded > 0 and currPop < aDP:  #this block -- add all mostly full HDs that are contig to growing list\n",
    "        nJustAdded = 0\n",
    "        canAddUset = set()\n",
    "        for u in addedUset:  #building all neighbors of in-HD munis\n",
    "            canAddUset = canAddUset.union(set(unitNbrs[u]) )\n",
    "        canAddUset = canAddUset.intersection( shouldAddUset.difference(addedUset) ) #whittling to eligible list\n",
    "        for u in canAddUset:\n",
    "            if currPop + 0.5 * unitPop[u] < 1.05 * aDP: #prevent big overadds\n",
    "                currPop += unitPop[u]\n",
    "                addedUset.add(u)\n",
    "                nJustAdded +=1\n",
    "            if currPop > 0.95 * aDP:  #it's OK if we go way over; we'll trim back later\n",
    "                break\n",
    "    # OK, we've added the 2/3 full munis.  Now add more contiguous partials if needed\n",
    "    eligibleSet = hasFracUset.difference(addedUset)\n",
    "    for u in list(eligibleSet):\n",
    "        if currPop + 0.5 * unitPop[u] > 1.05 * aDP:\n",
    "            eligibleSet.remove(u)\n",
    "    contigAddableSet = set()  #the eligible units adjacent to the current (growing) set of units\n",
    "    for u in addedUset:\n",
    "        contigAddableSet = contigAddableSet.union(set(unitNbrs[u]).intersection(eligibleSet))\n",
    "    while currPop < 0.95 * aDP and len(contigAddableSet) > 0:  #add close, mostly used munis\n",
    "        canAddUlist = list(contigAddableSet)\n",
    "        canAddScores = [ unitCP[u].distance(HDCP[h])/origL * (1. - useFrac[u]) for u in canAddUlist]\n",
    "        addIdx = canAddScores.index(np.min(canAddScores))\n",
    "        u = canAddUlist[addIdx]\n",
    "        currPop += unitPop[u]\n",
    "        addedUset.add(u)\n",
    "        contigAddableSet.remove(u)\n",
    "        eligibleSet.remove(u)\n",
    "        contigAddableSet = contigAddableSet.union(set(unitNbrs[u]).intersection(eligibleSet))\n",
    "        for u in list(contigAddableSet):\n",
    "            if currPop + 0.5 * unitPop[u] > 1.05 * aDP: #prevent big overadds\n",
    "                contigAddableSet.remove(u)\n",
    "    if currPop < 0.2 * aDP:\n",
    "        print(\"HD\",h,\" has only\",r3(currPop/aDP),\"pop/aDP. We will swell by nearest munis to shore it up\")\n",
    "        canAddUset = set(unitNbrs[homeU[h]])\n",
    "        for u in addedUset:\n",
    "            canAddUset = canAddUset.intersection(unitNbrs[u])\n",
    "        canAddUset = canAddUset.difference(addedUset)\n",
    "        while currPop < 0.95 * aDP and len(canAddUset) > 0:  #add close munis, biasing towards highly used\n",
    "            canAddUlist = list(canAddUset)\n",
    "            canAddScores = [ unitCP[u].distance(HDCP[h])/origL * (1. - useFrac[u]) for u in canAddUlist]\n",
    "            addIdx = canAddScores.index(np.min(canAddScores))\n",
    "            u = canAddUlist[addIdx]\n",
    "            currPop += unitPop[u]\n",
    "            addedUset.add(u)\n",
    "            canAddUset.remove(u)\n",
    "            for uu in unitNbrs[u]:\n",
    "                if useFrac[uu] > 0 and uu not in addedUset:\n",
    "                    canAddUset.add(uu)\n",
    "            for u in list(canAddUset):\n",
    "                if currPop + 0.5 * unitPop[u] > 1.05 * aDP: #prevent big overadds\n",
    "                    canAddUset.remove(u)\n",
    "\n",
    "    HDvPop[h] = currPop\n",
    "    HDunitList[h] = list(addedUset)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6ca0e286-f4bc-4153-8e53-42e5b6757339",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lets plot our muni-snapped HD pops vs. orig pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and compute current unit usage with these whole-unit, possibly discontig HDs\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"lets plot our muni-snapped HD pops vs. orig pops\")\n",
    "plt.scatter(HDvtdPop, HDvPop)\n",
    "plt.axhline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "print(\"and compute current unit usage with these whole-unit, possibly discontig HDs\")\n",
    "unitUse = [0.]*nUnits\n",
    "for h in popHDlist:\n",
    "    for u in HDunitList[h]:\n",
    "        unitUse[u] += nDistricts * HDwt[h]\n",
    "plt.hist(unitUse,weights=unitPop)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "81a441d0-3a2f-473d-ba3b-0c8b365dfb55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(unitPop,unitUse)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ecceb61d-a30b-4337-81cd-75fb7ef961af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if unitUse[u] < 0.4:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "30de9de6-e831-4cfa-a449-2cc7bf3d330f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "classify these muni HDs by contiguity\n",
      "quick classification: who has contiguity problems?\n",
      "working on HD 195 time is now 0\n",
      "working on HD 5239 time is now 1\n",
      "working on HD 44 time is now 3\n",
      "working on HD 991 time is now 4\n",
      "working on HD 2896 time is now 6\n",
      "working on HD 7822 time is now 6\n",
      "working on HD 2043 time is now 8\n",
      "working on HD 5182 time is now 9\n",
      "working on HD 3108 time is now 11\n",
      "working on HD 1961 time is now 13\n",
      "working on HD 715 time is now 14\n",
      "working on HD 6351 time is now 15\n",
      "working on HD 7035 time is now 17\n",
      "out of 8934 total HDs, there were 8934.0 contiguous and 8034.0 complement-contiguous HDs\n",
      "0 HDs had both discontiguity problems, while enclave-only = 900 and discontig only= 0\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 0 900\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"classify these muni HDs by contiguity\") #take from vanillaHD\n",
    "\n",
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6421f8ab-a699-4c29-976e-8c8e39d4597a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 154942 district pop vs 119186 target\n",
      "working on enclave-y HD 8420 . We have evaluated 0 of 900 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 846 . We have evaluated 200 of 900 enclavy HDs.Time is now 3\n",
      "working on enclave-y HD 5627 . We have evaluated 400 of 900 enclavy HDs.Time is now 5\n",
      "working on enclave-y HD 7006 . We have evaluated 600 of 900 enclavy HDs.Time is now 9\n",
      "working on enclave-y HD 1401 . We have evaluated 800 of 900 enclavy HDs.Time is now 13\n",
      "Out of 900 HDs with enclaves 900 had enclaves.\n",
      "Of these, 877 wouldn't be over 154942 if all enclaves filled, while 23 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#copy enclave fix here.  Will not have any muni-discontig\n",
    "### THIS IS THE \"CANFILL\" CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.3 * aDP) #wider tolerance here for munis vs. vtd-based\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",int(maxPostFixPop),\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(eLgenerator):\n",
    "    if iii%200 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(eLgenerator),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(eLgenerator),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "aced004d-abcf-4b9d-8249-332156a1759a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.02593 0.0893\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "HDweight = HDwt.copy()\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.01:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c06c0980-fad8-4596-bf2f-ad46bd6bb074",
   "metadata": {},
   "outputs": [],
   "source": [
    "savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "80050c17-7680-4ea9-b803-dfc5bc057e5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping\n",
    "HDunitList = [savedHDunitList[t].copy() for t in range(nHDs) ]   #restart\n",
    "HDvPop = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "plt.axvline(aDP, ls=\"--\")\n",
    "plt.axvline(0.95*aDP, ls=\"dotted\")\n",
    "plt.axvline(1.05*aDP, ls=\"dotted\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "827b8496-d66d-40ae-9780-a20243a54f92",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are the HD centers for 23 cantFill HDs with border or big enclaves\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are the HD centers for\",len(cantFill),\"cantFill HDs with border or big enclaves\")\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u],0.1)\n",
    "for t in cantFill:\n",
    "    plotPoly(HDCP[t].buffer(0.02))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d4eec53d-e431-4e8d-a430-31ef4d1aa8c7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 195\n",
      "working on avg unit-to-HDcp dist for HD 8027\n",
      "working on avg unit-to-HDcp dist for HD 6134\n",
      "working on avg unit-to-HDcp dist for HD 750\n",
      "working on avg unit-to-HDcp dist for HD 6298\n",
      "working on avg unit-to-HDcp dist for HD 395\n",
      "working on avg unit-to-HDcp dist for HD 458\n",
      "working on avg unit-to-HDcp dist for HD 3108\n",
      "working on avg unit-to-HDcp dist for HD 5585\n",
      "working on avg unit-to-HDcp dist for HD 5957\n",
      "working on avg unit-to-HDcp dist for HD 4309\n",
      "working on avg unit-to-HDcp dist for HD 8806\n",
      "all unit-toHDcp distances computed\n"
     ]
    }
   ],
   "source": [
    "barredJettisonSet = set([]) #for basic muni snap, there are no special corner units to freeze\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "print(\"all unit-toHDcp distances computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "76225203-dcf1-4845-b6a2-3b75e3749b01",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for muniSnap99 code, all units are munis, not clusters\n"
     ]
    }
   ],
   "source": [
    "print(\"for muniSnap99 code, all units are munis, not clusters\")\n",
    "allUnits = [u for u in range(nUnits)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "42d45847-2d8f-40aa-ae1b-91fb65ba3810",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this code will solve large enclaves so HD and complement are contiguous for 23 HDs\n",
      "working on HD 2242 cantFill 0 of 23 .Time is now 0\n",
      "working on HD 2945 cantFill 20 of 23 .Time is now 0\n",
      "WARNING - we lost home unit 75 from HD 4494\n",
      "after the MustFree code run, we have the following for cluster usage\n",
      "current avg use and its sd are 1.02594 0.08909\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#THIS IS THE MUSTFREE CODE - for high-pop HDs with map-border enclaves, can't fill; \n",
    "#  must jettison some inHD map-boundary units to connect the enclave to the larger complement\n",
    "#For each HD to be triaged, define the list(s) of contiguous enclave units that are on the map boundary, \n",
    "#  and the in-HD map-boundary segments.  ID which in-HD MBS's adjoin one vs. two enclaves.\n",
    "#     Fill all internal enclaves, and all boundary enclaves < 0.05 aDP.\n",
    "#   Then each loop, look for boundary enclaves that can be filled without overpopping.\n",
    "#     If none, pick the 1/2 has-1-boundary-enclave-neighbor that is least painful to jettison to free an enclave.\n",
    "#       (Jettison score based on pop-to-Free and distance from HDcP)\n",
    "#         Update HDpop, HDlist, and enclave & HD-boundary associations, then re-loop\n",
    "# Later, we will swell-fill to square up pop (w/ checkEnclave) biasing toward close-to-hdCP, underused\n",
    "borderSet = set(borderUnits)\n",
    "debug, debugPlot = False, False\n",
    "startTime = time.time()  #takes about 1.5sec per HD triage\n",
    "clusterJettisonBoost = 3.  #this discourages jettisoning of underused clusters\n",
    "print(\"this code will solve large enclaves so HD and complement are contiguous for\",len(cantFill),\"HDs\")\n",
    "nEnclavesPerHD = [0 for t in range(nHDs)]\n",
    "HDenclaveLists = [list() for t in range(nHDs)]\n",
    "for iii,t in enumerate(cantFill):\n",
    "    if iii %20 == 0:\n",
    "        print(\"working on HD\",t,\"cantFill\",iii,\"of\",len(cantFill),\".Time is now\",int(time.time() - startTime) )\n",
    "    shedUs = list()    \n",
    "    enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    nEnclavesPerHD[t] = len(enclaveLists)\n",
    "    HDenclaveLists[t] = enclaveLists.copy()\n",
    "    if debug:\n",
    "        print(\"pre-adjust HDpop for HD\",t,\"is\",HDvPop[t],\"I found\",len(enclaveLists),\"TOTAL enclaves\")\n",
    "    internalEnclaves, edgeEnclaves, combinedEnclBorderList = list(), list(), list()\n",
    "    for jjj, eL in enumerate(enclaveLists.copy() ):\n",
    "        enclaveBorderList = list ( set(eL).intersection(borderSet) )\n",
    "        if debug:\n",
    "            print(\"In enclave\",jjj,\"I found\",len(enclaveBorderList),\"units that were enclaved and are in the map borderSet\")\n",
    "        combinedEnclBorderList += enclaveBorderList\n",
    "        ePop = np.sum( [unitPop[u] for u in eL] )\n",
    "        if len(enclaveBorderList) == 0 or ePop < 0.05 * aDP:  #internal or small enclave.  Fill it\n",
    "            if ePop > 0:  #in a prev treatment, could be an empty (surrounded) unit that we don't care about\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += ePop\n",
    "            internalEnclaves.append(eL)\n",
    "        else:\n",
    "            edgeEnclaves.append(eL)\n",
    "    if debug:\n",
    "        print(\"Of these\",len(internalEnclaves),\"were internal or small, so I filled them, leaving\",\n",
    "              len(edgeEnclaves),\"non-small border = edge enclaves\" )\n",
    "    if debugPlot:\n",
    "        print(\"Here is the original HD, internal enclaves ('x') and non-small border enclaves by enclave no\")\n",
    "        plotPoly(hdCP[t].buffer(0.3))\n",
    "        for u in HDunitList[t]:\n",
    "            if unitPop[u] > 0:\n",
    "                plotPoly(unitGeom[u],0.2)\n",
    "        for L in internalEnclaves:\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u],1.5)\n",
    "                    plotCenter(\"x\",unitCP[u],8)\n",
    "        for L in edgeEnclaves: #############\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u])\n",
    "                    #plotCenter(\"e\",unitCP[u],8)\n",
    "        #plotPoly(MAP,0.4)\n",
    "        #plt.show()\n",
    "    enclaveLists, combinedEnclBorderSet = list(), set(combinedEnclBorderList)\n",
    "    if len(edgeEnclaves) > 0:\n",
    "        # Now, we order by chain connectivity of HD and enclave sublists to be H0-E0-H1-E1 ... En-Hn+1\n",
    "        nonHDborderSet = borderSet.difference(  set(HDunitList[t]) )\n",
    "        nonHDlongBorderSet = nonHDborderSet.difference(combinedEnclBorderSet) #long=non HD boundary excluding enclaves\n",
    "        remainingEnclBorderSet = combinedEnclBorderSet.copy()\n",
    "        remainingHDborderSet =   borderSet.intersection(set(HDunitList[t]) )\n",
    "        #Now find the \"HDender\" unit which borders the non-enclave nonHD boundary, then find opp end of this HD bdry piece\n",
    "        HDender = list(set(getAdjoiners(nonHDlongBorderSet,unitNbrs)).intersection(remainingHDborderSet) )[0]\n",
    "        firstHDborderSet = getContigFromStarter(HDender,remainingHDborderSet,unitNbrs)\n",
    "        HDstarter = list(set(getAdjoiners(remainingEnclBorderSet,unitNbrs)).intersection(firstHDborderSet))[0]\n",
    "        HDborderSublists = [ list(firstHDborderSet) ]\n",
    "        unused = [1 for eL in edgeEnclaves]\n",
    "        eLadjoiners = [getAdjoiners(eL,unitNbrs) for eL in edgeEnclaves ]\n",
    "        for j in range(len(edgeEnclaves)): #find the enclave with the most HDstarter neighbors (at least 1)\n",
    "            found = False\n",
    "            for i,eL in enumerate(edgeEnclaves):\n",
    "                if unused[i] == 1:\n",
    "                    HDadjSet = set(HDborderSublists[j]).intersection(set(eLadjoiners[i]))\n",
    "                    if len(HDadjSet) > 0:\n",
    "                        unused[i] = 0\n",
    "                        eNo = i\n",
    "                        found = True\n",
    "                        remainingEnclBorderSet = remainingEnclBorderSet.difference(set(edgeEnclaves[eNo]) )\n",
    "                        enclaveLists.append(edgeEnclaves[eNo])\n",
    "                        remainingHDborderSet = remainingHDborderSet.difference(set(HDborderSublists[j]) )\n",
    "                        if len(remainingHDborderSet) > 0: #for narrow peninsulas, separated border units may connect\n",
    "                            #this if statement was added for legisl OH\n",
    "                            HDstarter = list(set(eLadjoiners[i]).intersection(remainingHDborderSet))[0]       \n",
    "                            HDborderSublists.append(getContigFromStarter(HDstarter,remainingHDborderSet,unitNbrs) )\n",
    "                        break\n",
    "                if found:\n",
    "                    break\n",
    "\n",
    "        enclavePops = [np.sum([unitPop[u] for u in L]) for L in enclaveLists]\n",
    "        #print(\"prior to adjustments, border enclavePops are\",enclavePops)         \n",
    "\n",
    "        nHDBS, nEnclaves = len(HDborderSublists), len(enclaveLists)\n",
    "        popToFree, freeingCounties, freeingUnits = [0. for n in range(nHDBS)], [list() for n in range(nHDBS) \n",
    "                                                                               ],[list() for n in range(nHDBS)]\n",
    "        for j,L in enumerate(HDborderSublists):\n",
    "            for u in L:\n",
    "                if int(allUnits[u]) == allUnits[u]:  #this border unit is a standard unit ##vtd in vanilla code\n",
    "                    c = countyNo[u] #countyNo[parentVTDno[allUnits[u]]]   #countyNo[allUnits[u]]\n",
    "                    if c not in freeingCounties[j]:\n",
    "                        if \"weDistinguishTinyCounties\" == \"yup\": #countyPop[c] < 0.1 * aDP: ##plan to add all in-county pop\n",
    "                            freeingCounties[j].append(c)\n",
    "                        else:\n",
    "                            popToFree[j] += unitPop[u]\n",
    "                            freeingUnits[j].append(u)\n",
    "                else: #border unit is a full county or cluster, or in a dense county.  Add the whole unit pop\n",
    "                    popToFree[j] += unitPop[u]\n",
    "                    freeingUnits[j].append(u)\n",
    "            for c in freeingCounties[j]:  #include ALL in-HD pop from each non-unit border county, not just its border units\n",
    "                #plotPoly(countyGeom[c],0.1)\n",
    "                for u in countyUnitList[c]:\n",
    "                    if u in HDunitList[t]:\n",
    "                        popToFree[j] += unitPop[u]\n",
    "                        freeingUnits[j].append(u)\n",
    "        freeingCP = [ getHDcp(  unitCP, unitPop, L) for L in freeingUnits ]\n",
    "        freeingScore = [ pTF/aDP - 0.5*freeingCP[j].distance(hdCP[t]) / avgDist[t] for j,pTF in enumerate(popToFree) ]\n",
    "        for j, fU in enumerate(freeingUnits):  #in above 0.5 is a fudgy\n",
    "            if len(barredJettisonSet.intersection(set(fU)) ) > 0: #has a cluster we want to hold onto\n",
    "                freeingScore[j] += clusterJettisonBoost #  ..so increase its score (make it harder to drop)\n",
    "        if debugPlot:\n",
    "            print(\"plotting the freeing units with negative numbers for each freeing group\")\n",
    "            for j,L in enumerate(freeingUnits):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        #plotPoly(unitGeom[u],0.5)\n",
    "                        plotCenter(\"-\"+str(j),unitGeom[u],6)\n",
    "                        pass\n",
    "            print(\"plotting the enclaveLists, with + numbers for each enclave\")\n",
    "            for j,L in enumerate(enclaveLists):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        plotPoly(unitGeom[u])\n",
    "                        plotCenter(j,unitCP[u],8)\n",
    "                        pass\n",
    "    \n",
    "    while len(enclaveLists) > 0:\n",
    "        if HDvPop[t] + np.min(enclavePops) < 1.05*aDP or np.min(enclavePops) < 0.05 * aDP:  #fill the smallest enclave\n",
    "            eNo = enclavePops.index(np.min(enclavePops))\n",
    "            HDunitList[t] += enclaveLists[eNo]\n",
    "            HDvPop[t] += enclavePops[eNo]\n",
    "            #print(t,\"=t. Absorbing enclave\",eNo,\"with pop\",enclavePops[eNo],\"HD total pop now\",int(HDfreePop[t]) )\n",
    "            enclaveBUs = list(set(enclaveLists[eNo]).intersection(set(borderUnits)) )\n",
    "            enclaveBpop = np.sum([unitPop[u] for u in enclaveBUs])\n",
    "            sNo, dropped_sNo = eNo, eNo+1\n",
    "            freeingScore[sNo] += freeingScore[sNo+1]+enclaveBpop/aDP\n",
    "            freeingUnits[sNo] += freeingUnits[sNo+1]+enclaveBUs\n",
    "            popToFree[sNo]    +=    popToFree[sNo+1]+enclaveBpop\n",
    "        else: #jettison one of the two end HD border lists; pick the less painful path to freedom\n",
    "            distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "            starterU = homeU[t] #HDunitList[t][distList.index(np.min(distList))]  #update from vanilla HD\n",
    "            eNo, dropped_sNo = 0,0\n",
    "            if starterU not in freeingUnits[-1]:  #we can't drop the home unit, even to save an underused corner\n",
    "                if freeingScore[-1] < freeingScore[0] or starterU in freeingUnits[0]:\n",
    "                    eNo, dropped_sNo = len(enclaveLists)-1,len(enclaveLists)\n",
    "            barredIncluded0 = barredJettisonSet.intersection(set(freeingUnits[0]))\n",
    "            barredIncluded_1 = barredJettisonSet.intersection(set(freeingUnits[-1]))\n",
    "            #if len(barredIncluded0.union(barredIncluded_1)) > 0:\n",
    "            #    print(\"We are considering dropping an end unit to free from t\",t,\". Chosen, beg, end, scores are\")\n",
    "            #    print(dropped_sNo,barredIncluded0, barredIncluded_1, freeingScore[0], freeingScore[-1])\n",
    "            HDunitList[t] = list( set(HDunitList[t]).difference(set(freeingUnits[dropped_sNo]) ) )\n",
    "            HDvPop[t] -= popToFree[dropped_sNo]\n",
    "            #print(t,\"= t. Jettisoning HDborder\",dropped_sNo,\"with popToFree\",popToFree[dropped_sNo] )\n",
    "        del enclaveLists[eNo]\n",
    "        del enclavePops[eNo]\n",
    "        if debug:\n",
    "            print(t,\"= t. Now we have\",len(enclaveLists),\"left trapped.  Picked eNo, freeScores were\", eNo,freeingScore)\n",
    "        del freeingScore[dropped_sNo]\n",
    "        del freeingUnits[dropped_sNo]\n",
    "        del popToFree   [dropped_sNo] \n",
    "\n",
    "    #plotPoly(MAP,0.4)\n",
    "    if debugPlot:\n",
    "        plt.show()    \n",
    "        \n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t]*nDistricts\n",
    "print(\"after the MustFree code run, we have the following for cluster usage\")\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "a9ce266b-3b8f-4ac5-863f-e01ca9083ccc",
   "metadata": {},
   "outputs": [],
   "source": [
    "lostHomeUlist = list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "e185112e-5993-458d-8041-3c7c94ad16fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "lostHomeUlist.append(4494)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "597a6d42-0310-4544-b7ce-543a90d09dca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "classify updated muni HDs by contiguity\n",
      "quick classification: who has contiguity problems?\n",
      "working on HD 195 time is now 0\n",
      "working on HD 5239 time is now 0\n",
      "working on HD 44 time is now 0\n",
      "working on HD 991 time is now 1\n",
      "working on HD 2896 time is now 1\n",
      "working on HD 7822 time is now 2\n",
      "working on HD 2043 time is now 2\n",
      "working on HD 5182 time is now 2\n",
      "working on HD 3108 time is now 3\n",
      "working on HD 1961 time is now 3\n",
      "working on HD 715 time is now 4\n",
      "working on HD 6351 time is now 4\n",
      "working on HD 7035 time is now 5\n",
      "out of 8934 total HDs, there were 8934.0 contiguous and 8934.0 complement-contiguous HDs\n",
      "0 HDs had both discontiguity problems, while enclave-only = 0 and discontig only= 0\n"
     ]
    }
   ],
   "source": [
    "print(\"classify updated muni HDs by contiguity\") #take from vanillaHD\n",
    "\n",
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "if len(smallPieceLists) + len(enclaveLists) > 0:\n",
    "    print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "          len(smallPieceLists),len(enclaveLists) )\n",
    "    plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "             cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "    plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "             cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "    plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "    plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "    plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d5ff711c-4bf6-437e-89fe-f30dda1a51a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "let's visualize over-used and underused units, < 0.75 or > 1.25\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here is the histogram of HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "minUnitUse, maxUnitUse = 0.75, 1.25\n",
    "print(\"let's visualize over-used and underused units, <\",minUnitUse,\"or >\",maxUnitUse)\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minUnitUse:\n",
    "        plotPoly(unitGeom[u],0.4)\n",
    "        plotCenter(\"u\",unitCP[u])\n",
    "    if unitUse[u] > maxUnitUse:\n",
    "        plotPoly(unitGeom[u], 1.5)\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c],0.1)\n",
    "plt.show()\n",
    "print(\"and here is the histogram of HD pops\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins = [0, 0.6*aDP, 0.7*aDP, 0.85*aDP, 0.9*aDP, 0.95*aDP,\n",
    "         0.98*aDP, aDP, 1.02*aDP, 1.05*aDP, 1.1*aDP, 1.15*aDP, 1.3*aDP, 1.5*aDP, 2.0*aDP])\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c2428bb3-f225-4e1f-aacb-abba4cc2cffb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before patching, make another copy of the current HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pre-patch avg use and its sd are 1.02594 0.08909\n"
     ]
    }
   ],
   "source": [
    "print(\"before patching, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        latestHDpop[t] += unitPop[u]\n",
    "        latestUnitUse[u] += nDistricts * HDweight[t]\n",
    "latestUnitWeights, latestUnitDistro = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "id": "1d0dcc8a-d0fc-48a9-bc6c-64d6041c288f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#HDunitList[t] = latestHDlist[t].copy() #restart\n",
    "#HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6b3dd3ff-706e-4e0d-a705-3a82cd62b519",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now square up the 223 HDs with pop < 113227 to within 5959\n",
      "working on squaring up HD 78 time is now 0\n",
      "working on squaring up HD 4809 time is now 0\n",
      "working on squaring up HD 7919 time is now 0\n",
      "We have attempted to address underpop in a total of 223 HDs\n",
      "Here is a scatterplot of original (x) to final pop (y)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING UP UNDERPOPPED\n",
    "HDnAddedUnits, HDaddedPop = [0]*nHDs, [0.]*nHDs\n",
    "underPoppedList, stillUnderPoppedList = list(),list()\n",
    "minDistrictPop, maxDistrictPop = 0.95 * aDP, 1.05 * aDP\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop < minDistrictPop and t in popHDlist:\n",
    "        underPoppedList.append(t)\n",
    "maxGap = maxDistrictPop - aDP \n",
    "print(\"We will now square up the\",len(underPoppedList),\"HDs with pop <\",int(minDistrictPop),\"to within\",int(maxGap) )\n",
    "startTime = time.time()\n",
    "for ii,t in enumerate(underPoppedList):\n",
    "    if ii%100 == 0:\n",
    "        print(\"working on squaring up HD\",t,\"time is now\",int(time.time() - startTime)) \n",
    "    gap = aDP - HDvPop[t]\n",
    "    origGap = gap\n",
    "    nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap:\n",
    "                nearHDlist.append(uu)   #below line: bias toward close, underused\n",
    "                nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  \n",
    "    currList = HDunitList[t].copy()\n",
    "    addedList = list()\n",
    "    stillGoing = True\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd: \n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else:\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  #bias toward close, underused\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    HDunitList[t] += addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n",
    "    HDaddedPop[t] = np.sum( [unitPop[u] for u in addedList] )\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has overshot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after adding\",HDaddedPop[t] )\n",
    "    if HDvPop[t] < minDistrictPop:\n",
    "        stillUnderPoppedList.append(t)\n",
    "print(\"We have attempted to address underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "if len(stillUnderPoppedList) > 0:\n",
    "    print(\"... but we got stuck in\",len(stillUnderPoppedList))\n",
    "print(\"Here is a scatterplot of original (x) to final pop (y)\")\n",
    "plt.scatter([HDvPop[t] - HDaddedPop[t] for t in underPoppedList], [HDvPop[t] for t in underPoppedList])\n",
    "plt.axhline(y=aDP, xmin = 0.9*aDP, xmax = 1.1*aDP, ls=\"--\")\n",
    "plt.axvline(x=aDP, ymin = 0.9*aDP, ymax = 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "72398364-3e4a-4a03-a2cf-58a21bdea412",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "previous unit avg and sd usage are 1.02594 0.08909\n",
      "amped unit avg and sd usage are 1.02742 0.08877\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prevUnitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        prevUnitUse[u] += HDweight[t] * nDistricts\n",
    "\n",
    "ampedUnitUse = [0. for u in range(nUnits)]\n",
    "ampedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "ampedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in ampedHDlist[t]:\n",
    "        ampedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "plt.hist(prevUnitUse,bins=50,weights=unitPop,label=\"previous\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.legend()\n",
    "ampedUnitUseAvg, ampedUnitUseSD = getWeightedAvgAndSD(ampedUnitUse,unitPop)\n",
    "print(\"previous unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f703cd30-fc17-4e4e-a458-40d9c74b266b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\n",
      "Let's now square down the 2451 overPopped HDs to within 5959\n",
      "working on squaring down HD 1 time is now 0\n",
      "can't drop any more units to HD 934 without creating an enclave\n",
      "can't drop any more units to HD 995 without creating an enclave\n",
      "working on squaring down HD 1028 time is now 0\n",
      "working on squaring down HD 1846 time is now 1\n",
      "working on squaring down HD 2816 time is now 2\n",
      "working on squaring down HD 3525 time is now 2\n",
      "working on squaring down HD 4199 time is now 4\n",
      "can't drop any more units to HD 4260 without creating an enclave\n",
      "working on squaring down HD 4742 time is now 5\n",
      "can't drop any more units to HD 5272 without creating an enclave\n",
      "working on squaring down HD 5431 time is now 6\n",
      "working on squaring down HD 6135 time is now 6\n",
      "working on squaring down HD 6782 time is now 7\n",
      "working on squaring down HD 7431 time is now 9\n",
      "working on squaring down HD 8184 time is now 10\n",
      "working on squaring down HD 8798 time is now 11\n",
      "can't drop any more units to HD 8873 without creating an enclave\n",
      "We have attempted to address underpop in a total of 2451 HDs\n",
      "Here is a scatterplot of original to final pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING DOWN\n",
    "print(\"Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\")\n",
    "HDnShedUnits = [0]*nHDs\n",
    "overPoppedList, stillOverPoppedList = list(), list()\n",
    "startTime = time.time()\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop > maxDistrictPop and t in popHDlist:\n",
    "        overPoppedList.append(t)\n",
    "\n",
    "maxGap = aDP - minDistrictPop   \n",
    "print(\"Let's now square down the\",len(overPoppedList),\"overPopped HDs to within\", int(maxGap))   \n",
    "for ii,t in enumerate(overPoppedList):\n",
    "    if ii%200 == 0:\n",
    "        print(\"working on squaring down HD\",t,\"time is now\",int(time.time()-startTime))\n",
    "    unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t],unitNbrs)\n",
    "    if not (unbroken and noEnclave):\n",
    "        print(\"SKIPPING shedding attempt on overpopped HD\",t,\"with pop\",HDvPop[t],\"because it was not legal to start\")\n",
    "    else:\n",
    "        excess = HDvPop[t] - aDP\n",
    "        origExcess = excess\n",
    "        HDboundaryList, HDboundaryScore = list(), list()  #these will be dynamic lists of the overused border units to jettison\n",
    "        #distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = homeU[t] #HDunitList[t][distList.index(np.min(distList))] #update from vanillaHD\n",
    "        barredSet = barredJettisonSet.union({starterU})\n",
    "        for u in set(HDunitList[t]).difference(barredSet):\n",
    "            isBoundary = False\n",
    "            for uu in unitNbrs[u]:\n",
    "                if uu not in HDunitList[t]:\n",
    "                    isBoundary = True\n",
    "                    break\n",
    "            if isBoundary and HDvPop[t] - unitPop[u] > aDP - maxGap:  #shedding this unit won't send us too far under targetpop\n",
    "                HDboundaryList.append(u)\n",
    "                HDboundaryScore.append((1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t])  #low-score = bias toward far, overused\n",
    "        currList = HDunitList[t].copy()\n",
    "        shedList, stillGoing = list(), True\n",
    "        while excess > maxGap and len(HDboundaryList) > 0 and stillGoing:   #shed the highest-scoring neighboring overused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(HDboundaryScore), 0, True\n",
    "            while i < len(HDboundaryScore) and notYetPicked and stillGoing:        \n",
    "                listNo = idx[i]   #low (large negative) score is preferred to shed\n",
    "                unitNoToShed = HDboundaryList[listNo]  # attempt to shed this unit ...\n",
    "                tryList = list(set(currList).difference( {unitNoToShed} ) )\n",
    "                unbroken, noEnclave, sPL, ePL = enclaveCheck(tryList,unitNbrs) \n",
    "                if unbroken and noEnclave:             #... if that won't eff up contiguity\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't drop any more units without creating an enclave\n",
    "                print(\"can't drop any more units to HD\",t,\"without creating an enclave\")\n",
    "            else: #add this eligible unit\n",
    "                shedList.append(unitNoToShed)\n",
    "                excess -= unitPop[unitNoToShed]        \n",
    "                del currList[currList.index(unitNoToShed) ]\n",
    "                del HDboundaryList[listNo]\n",
    "                del HDboundaryScore[listNo]\n",
    "                for u in unitNbrs[unitNoToShed]:      # ... and ID any neighboring units that will now be on boundary after we shed this unit\n",
    "                    if u in currList and u not in HDboundaryList and (unitPop[u] <= excess + maxGap and u not in barredSet): \n",
    "                        HDboundaryList.append(u)\n",
    "                        HDboundaryScore.append( (1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t] )  #low-score, bias toward far & overused       \n",
    "                for uu in HDboundaryList.copy():\n",
    "                    if unitPop[uu] > excess + maxGap:  #checking to see if the latest pop change DQ's any large units on current boundary\n",
    "                        del HDboundaryScore[HDboundaryList.index(uu)]\n",
    "                        del HDboundaryList[HDboundaryList.index(uu)]   \n",
    "        for u in shedList:\n",
    "            unitUse[u] -= HDweight[t] * nDistricts\n",
    "        HDunitList[t], HDvPop[t] = currList.copy(), np.sum( [unitPop[u] for u in currList ] )    \n",
    "        if HDvPop[t] < minDistrictPop:\n",
    "            print(\"Oops! HD\",t,\"now has undershot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after shedding\",\n",
    "                 np.sum([unitPop[u] for u in shedList]) )        \n",
    "        if HDvPop[t] < minDistrictPop:\n",
    "            stillOverPoppedList.append(t)\n",
    "        HDnShedUnits[t] = -1 * len(shedList)\n",
    "        if homeU[t] not in HDunitList[t]:\n",
    "            print(\"WARNING: we lost the home unit\",homeU[t],\"from HD\",HD)\n",
    "            lostHomeUlist.append(t)\n",
    "            \n",
    "print(\"We have attempted to address underpop in a total of\",len(overPoppedList),\"HDs\")\n",
    "if len(stillOverPoppedList) > 0:\n",
    "    print(\"... but we got stuck in\",len(stillOverPoppedList))\n",
    "print(\"Here is a scatterplot of original to final pop\")\n",
    "plt.scatter([ampedHDpop[t] for t in overPoppedList], [HDvPop[t] for t in overPoppedList])\n",
    "plt.axhline(aDP, 0.9*aDP, 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "9c4d12b3-8596-4a5b-937e-7ef8ed71a903",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updating our unitUse, underpopped and overpopped lists\n",
      "unit use histogram\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit use by pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we now have a total of 0 underpopped HDs and 105 overpopped HDs\n"
     ]
    }
   ],
   "source": [
    "print(\"updating our unitUse, underpopped and overpopped lists\")\n",
    "unitUse = [0.]*nUnits\n",
    "HDvPop = [0.]*nHDs\n",
    "stillUnder, stillOver = list(), list()\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "        HDvPop[t] += unitPop[u]\n",
    "    if HDvPop[t] < minDistrictPop:\n",
    "        stillUnder.append(t)\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        stillOver.append(t)\n",
    "print(\"unit use histogram\")\n",
    "plt.hist(unitUse, weights = unitPop)\n",
    "plt.show()\n",
    "print(\"unit use by pop\")\n",
    "plt.scatter(unitPop,unitUse)\n",
    "plt.show()\n",
    "print(\"we now have a total of\",len(stillUnder),\"underpopped HDs and\",len(stillOver),\"overpopped HDs\")\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "c7b7fff8-d72b-48b6-a1f3-e131d23f1adb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([unitPop[homeU[t]] for t in stillOver])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "3e80ff56-7d63-4aca-b84a-bae0cdc3d835",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are centerpoints of overpopped HDs\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are centerpoints of overpopped HDs\")\n",
    "for t in stillOver:\n",
    "    plotPoly(HDCP[t].buffer(0.02),1)\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c])\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 1.2 :\n",
    "        plotPoly(unitGeom[u],0.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "2bf4579a-03ec-43b0-9864-4aaafd3c8119",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of units in overpopped HDs by home muni pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nMunisInOverPs = [len(HDunitList[t]) for t in stillOver]\n",
    "plt.scatter([unitPop[homeU[t]] for t in stillOver],nMunisInOverPs)\n",
    "print(\"number of units in overpopped HDs by home muni pop\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "dc736ef8-0f54-4330-918c-e287db517f59",
   "metadata": {},
   "outputs": [],
   "source": [
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(homeU[t],\"unit is not in HD\",t)\n",
    "#I guess the homeU got picked back up in t=4494"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "ca142c7c-3145-48e8-aa67-bedbf70a40ab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "showing an example HD that needs a split\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"showing an example HD that needs a split\")\n",
    "t = stillOver[22]\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u])\n",
    "    plotCenter(r3(unitPop[u]/aDP),unitGeom[u])\n",
    "plotPoly(HDCP[t].buffer(0.01))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "4b80ba32-7526-4664-bfa0-2559a6c859cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most of these appear to be legit blocky areas\n",
      "We will therefore slice out a partial muni to meet aDP\n",
      "Histogram of number of splittable units in stuck overpopped HDs\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updated HDvPop histogram\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Most of these appear to be legit blocky areas\")\n",
    "print(\"We will therefore slice out a partial muni to meet aDP\")\n",
    "splitUnitNo, splitUnitFrac, hasSplitUnit = [-999]*nHDs, [0.]*nHDs, [0]*nHDs\n",
    "splitPops  = [0]*nHDs\n",
    "nSplittables = list()\n",
    "afterSplitHDvPop = HDvPop[t].copy()\n",
    "for t in stillOver:\n",
    "    splittables = list()\n",
    "    for u in HDunitList[t]:\n",
    "        if u != homeU[t] and u not in unsplittableUnits:\n",
    "            contig,cContig, __, ___ = enclaveCheck(list(set(HDunitList[t]).difference({u})), unitNbrs)\n",
    "            if contig and cContig: #jetting this unit doesn't create a hole or discontig\n",
    "                splittables.append(u)\n",
    "            else:\n",
    "                if len(set(unitNbrs[u]).difference(set(HDunitList[t]))) > 1: #this unit is not surrounded by the HD\n",
    "                    splittables.append(u)  #so we can imagine a partial that maintains contiguity; no enclave\n",
    "    if len(splittables) == 0:\n",
    "        print(\"We are having trouble finding a legit splittable for HD\",t)\n",
    "        for u in HDunitList[t]:\n",
    "            plotPoly(unitGeom[u])\n",
    "            plotCenter(r3(unitPop[u]/aDP),unitGeom[u])\n",
    "        plotPoly(HDCP[t].buffer(0.01))\n",
    "        plt.show()\n",
    "    nSplittables.append(len(splittables))\n",
    "    if len(splittables) > 0:  #pick the farthest one away to split\n",
    "        splitDist = [unitCP[u].distance(HDCP[t]) for u in splittables ]\n",
    "        splitU = splittables[splitDist.index(np.max(splitDist)) ]\n",
    "        hasSplitUnit[t] = 1\n",
    "        splitUnitNo[t] = splitU\n",
    "        droppedPop = HDvPop[t] - 0.5*(aDP + maxDistrictPop)\n",
    "        keptPop = unitPop[splitU] - droppedPop  #waffle between min splitting and target pop for this HD\n",
    "        splitUnitFrac[t] = keptPop / unitPop[splitU]\n",
    "        afterSplitHDvPop[t] -= droppedPop\n",
    "        \n",
    "print(\"Histogram of number of splittable units in stuck overpopped HDs\")\n",
    "plt.hist(nSplittables)\n",
    "plt.show()\n",
    "\n",
    "print(\"projected aftersplit HDvPop histogram\")\n",
    "plt.hist([afterSplitHDvPop[t] for t in popHDlist],weights=[HDweight[t] for t in popHDlist])\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.axvline(0.95*aDP, ls=\"dotted\")\n",
    "plt.axvline(1.05*aDP, ls=\"dotted\")\n",
    "plt.show()\n",
    "                "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "630ef73f-d415-4142-b365-b84c6b7f9e6d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick confirmation: any contiguity problems?\n",
      "working on HD 195 time is now 0\n",
      "working on HD 5239 time is now 0\n",
      "working on HD 44 time is now 0\n",
      "working on HD 991 time is now 1\n",
      "working on HD 2896 time is now 1\n",
      "working on HD 7822 time is now 2\n",
      "working on HD 2043 time is now 2\n",
      "working on HD 5182 time is now 2\n",
      "working on HD 3108 time is now 3\n",
      "working on HD 1961 time is now 3\n",
      "working on HD 715 time is now 4\n",
      "working on HD 6351 time is now 4\n",
      "working on HD 7035 time is now 5\n",
      "out of 8934 total HDs, there were 8934.0 contiguous and 8934.0 complement-contiguous HDs\n",
      "0 HDs had both discontiguity problems, while enclave-only = 0 and discontig only= 0\n"
     ]
    }
   ],
   "source": [
    "print(\"quick confirmation: any contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):   \n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "9436e8b9-e204-41c0-96d3-b5eef5b118c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updating our unitUse, underpopped and overpopped lists\n",
      "unit use histogram\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the number of stillUnder and stillOver HDs is 0 105\n"
     ]
    }
   ],
   "source": [
    "print(\"updating our unitUse, underpopped and overpopped lists\")\n",
    "unitUse = [0.]*nUnits\n",
    "stillUnder, stillOver = list(), list()\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "    if hasSplitUnit[t] == 1:\n",
    "        unitUse[splitUnitNo[t]] -= (1. - splitUnitFrac[t]) * nDistricts * HDweight[t]\n",
    "    if HDvPop[t] < minDistrictPop:\n",
    "        stillUnder.append(t)\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        stillOver.append(t)\n",
    "print(\"unit use histogram\")\n",
    "plt.hist(unitUse, weights = unitPop)\n",
    "plt.show()\n",
    "print(\"the number of stillUnder and stillOver HDs is\",len(stillUnder),len(stillOver) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "78d8647b-5421-4a27-889f-27315e9e7695",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "... and our usage vs. pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"... and our usage vs. pop\")\n",
    "plt.scatter(unitPop,unitUse)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "e5bba0ce-dc4a-494e-86b3-0fbefed0e032",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For now, we will freeze the HDs with split units prior to patching.\n",
      "Start with underpatching. This algorithm simplified vs. vanillaHD to manage blockiness.\n",
      "Currently, we will stop patching when the overall sd of usage is less than 0.055\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated maxSD value 0.055\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this would currently cover a total of 1147 units\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated number of units to try boosting usage 500\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 1961 units out of 3442 with usage below 0.98\n",
      "maxExchangePop is currently 0.25 fraction of avgDistrictPop\n",
      "Let's further tighten the distro with exchanges up to 29796 = aDP* 0.25\n",
      "current avg and SD of unit usage are 0.99944 0.09929 . Now trying to increase up to 500 units' underusage\n",
      "all done trying2increase usage of unit 1090 final usage = 0.68223 2 sec elapsed 24 66 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 0.99952 0.09847\n",
      "all done trying2increase usage of unit 3438 final usage = 0.98332 3 sec elapsed 30 88 complete, failed patches, unstarted= 7\n",
      "current avg and SD of usage are 0.99951 0.09773\n",
      "all done trying2increase usage of unit 758 final usage = 0.98656 6 sec elapsed 22 86 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 0.99949 0.09643\n",
      "all done trying2increase usage of unit 1343 final usage = 0.98457 7 sec elapsed 20 76 complete, failed patches, unstarted= 5\n",
      "current avg and SD of usage are 0.99945 0.09573\n",
      "all done trying2increase usage of unit 1521 final usage = 0.86868 8 sec elapsed 18 15 complete, failed patches, unstarted= 20\n",
      "current avg and SD of usage are 0.99945 0.09534\n",
      "all done trying2increase usage of unit 190 final usage = 0.98465 10 sec elapsed 25 100 complete, failed patches, unstarted= 6\n",
      "current avg and SD of usage are 0.99953 0.09416\n",
      "all done trying2increase usage of unit 1943 final usage = 0.94234 12 sec elapsed 16 37 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99953 0.09364\n",
      "all done trying2increase usage of unit 2635 final usage = 0.9371 23 sec elapsed 24 46 complete, failed patches, unstarted= 8\n",
      "current avg and SD of usage are 0.99951 0.09304\n",
      "all done trying2increase usage of unit 1039 final usage = 0.75293 24 sec elapsed 1 85 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 0.99952 0.09301\n",
      "begin usage increase for unit 424 with usage 0.74863 . Sec, total UU units tried = 24 10\n",
      "all done trying2increase usage of unit 424 final usage = 0.98177 27 sec elapsed 21 46 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99957 0.09209\n",
      "all done trying2increase usage of unit 1764 final usage = 0.99035 28 sec elapsed 19 20 complete, failed patches, unstarted= 22\n",
      "current avg and SD of usage are 0.99962 0.09134\n",
      "all done trying2increase usage of unit 1778 final usage = 0.98282 29 sec elapsed 20 10 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 0.99967 0.09069\n",
      "all done trying2increase usage of unit 2655 final usage = 0.99038 31 sec elapsed 19 53 complete, failed patches, unstarted= 6\n",
      "current avg and SD of usage are 0.99969 0.0899\n",
      "all done trying2increase usage of unit 532 final usage = 0.98464 31 sec elapsed 17 6 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99971 0.08957\n",
      "all done trying2increase usage of unit 534 final usage = 0.98819 37 sec elapsed 21 122 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 0.99976 0.08902\n",
      "all done trying2increase usage of unit 3421 final usage = 0.93418 40 sec elapsed 15 65 complete, failed patches, unstarted= 17\n",
      "current avg and SD of usage are 0.99975 0.08856\n",
      "all done trying2increase usage of unit 188 final usage = 0.98878 42 sec elapsed 21 84 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99976 0.0884\n",
      "all done trying2increase usage of unit 182 final usage = 1.00254 43 sec elapsed 17 33 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99975 0.08782\n",
      "all done trying2increase usage of unit 1016 final usage = 0.98003 44 sec elapsed 19 31 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99981 0.08758\n",
      "begin usage increase for unit 2701 with usage 0.77287 . Sec, total UU units tried = 45 20\n",
      "all done trying2increase usage of unit 2701 final usage = 0.89535 55 sec elapsed 14 80 complete, failed patches, unstarted= 17\n",
      "current avg and SD of usage are 0.99984 0.08719\n",
      "all done trying2increase usage of unit 531 final usage = 0.86272 56 sec elapsed 9 59 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99983 0.08683\n",
      "all done trying2increase usage of unit 1479 final usage = 0.98239 58 sec elapsed 19 52 complete, failed patches, unstarted= 4\n",
      "current avg and SD of usage are 0.99982 0.08537\n",
      "all done trying2increase usage of unit 389 final usage = 0.98437 58 sec elapsed 18 15 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99983 0.08364\n",
      "all done trying2increase usage of unit 735 final usage = 0.94005 59 sec elapsed 19 23 complete, failed patches, unstarted= 20\n",
      "current avg and SD of usage are 0.99986 0.08339\n",
      "all done trying2increase usage of unit 443 final usage = 0.983 61 sec elapsed 23 19 complete, failed patches, unstarted= 20\n",
      "current avg and SD of usage are 0.9999 0.08285\n",
      "all done trying2increase usage of unit 635 final usage = 0.97799 62 sec elapsed 18 122 complete, failed patches, unstarted= 31\n",
      "current avg and SD of usage are 0.99988 0.0824\n",
      "all done trying2increase usage of unit 207 final usage = 0.98745 64 sec elapsed 18 21 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99986 0.08182\n",
      "all done trying2increase usage of unit 1347 final usage = 0.98139 65 sec elapsed 16 15 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99992 0.08153\n",
      "all done trying2increase usage of unit 3377 final usage = 0.9871 68 sec elapsed 15 12 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99989 0.08046\n",
      "begin usage increase for unit 2621 with usage 0.79956 . Sec, total UU units tried = 68 30\n",
      "all done trying2increase usage of unit 2621 final usage = 0.94196 70 sec elapsed 13 43 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 0.99991 0.08002\n",
      "all done trying2increase usage of unit 2509 final usage = 0.99019 72 sec elapsed 16 38 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 0.99993 0.07965\n",
      "all done trying2increase usage of unit 979 final usage = 0.98209 74 sec elapsed 18 27 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00002 0.07927\n",
      "all done trying2increase usage of unit 2709 final usage = 0.93314 82 sec elapsed 12 62 complete, failed patches, unstarted= 3\n",
      "current avg and SD of usage are 1.00005 0.07883\n",
      "all done trying2increase usage of unit 3354 final usage = 0.98521 84 sec elapsed 16 50 complete, failed patches, unstarted= 27\n",
      "current avg and SD of usage are 1.0001 0.07868\n",
      "all done trying2increase usage of unit 610 final usage = 0.98889 86 sec elapsed 16 24 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00019 0.07833\n",
      "all done trying2increase usage of unit 1086 final usage = 0.98647 88 sec elapsed 17 9 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00026 0.07795\n",
      "all done trying2increase usage of unit 3437 final usage = 0.98841 89 sec elapsed 17 11 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00025 0.07761\n",
      "all done trying2increase usage of unit 597 final usage = 0.98636 94 sec elapsed 16 117 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00027 0.07661\n",
      "all done trying2increase usage of unit 122 final usage = 0.99394 97 sec elapsed 13 27 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00033 0.07596\n",
      "begin usage increase for unit 1001 with usage 0.81467 . Sec, total UU units tried = 97 40\n",
      "all done trying2increase usage of unit 1001 final usage = 0.99092 98 sec elapsed 16 27 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00037 0.07592\n",
      "all done trying2increase usage of unit 699 final usage = 0.99224 99 sec elapsed 17 24 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.0004 0.07583\n",
      "all done trying2increase usage of unit 39 final usage = 0.98808 102 sec elapsed 16 66 complete, failed patches, unstarted= 6\n",
      "current avg and SD of usage are 1.00045 0.07525\n",
      "all done trying2increase usage of unit 84 final usage = 0.97996 103 sec elapsed 13 102 complete, failed patches, unstarted= 17\n",
      "current avg and SD of usage are 1.00049 0.07513\n",
      "all done trying2increase usage of unit 1866 final usage = 0.98211 104 sec elapsed 9 17 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00046 0.0745\n",
      "all done trying2increase usage of unit 94 final usage = 0.9909 105 sec elapsed 17 37 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00042 0.07393\n",
      "all done trying2increase usage of unit 234 final usage = 0.98469 107 sec elapsed 17 16 complete, failed patches, unstarted= 8\n",
      "current avg and SD of usage are 1.00048 0.07359\n",
      "all done trying2increase usage of unit 956 final usage = 0.98661 109 sec elapsed 14 37 complete, failed patches, unstarted= 15\n",
      "current avg and SD of usage are 1.00052 0.07324\n",
      "all done trying2increase usage of unit 1008 final usage = 0.98584 109 sec elapsed 12 13 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00048 0.07292\n",
      "all done trying2increase usage of unit 3353 final usage = 0.98979 111 sec elapsed 12 135 complete, failed patches, unstarted= 6\n",
      "current avg and SD of usage are 1.00047 0.07297\n",
      "begin usage increase for unit 1358 with usage 0.83283 . Sec, total UU units tried = 111 50\n",
      "all done trying2increase usage of unit 1358 final usage = 0.98036 113 sec elapsed 19 9 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00053 0.07268\n",
      "all done trying2increase usage of unit 2530 final usage = 0.9846 114 sec elapsed 12 11 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00052 0.07256\n",
      "all done trying2increase usage of unit 937 final usage = 0.98609 115 sec elapsed 15 60 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00053 0.07187\n",
      "all done trying2increase usage of unit 1463 final usage = 0.87321 115 sec elapsed 5 23 complete, failed patches, unstarted= 9\n",
      "current avg and SD of usage are 1.00054 0.07175\n",
      "all done trying2increase usage of unit 88 final usage = 0.99063 117 sec elapsed 11 23 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00059 0.07125\n",
      "all done trying2increase usage of unit 862 final usage = 0.98629 120 sec elapsed 14 129 complete, failed patches, unstarted= 5\n",
      "current avg and SD of usage are 1.00061 0.07082\n",
      "all done trying2increase usage of unit 447 final usage = 0.99071 121 sec elapsed 13 19 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00062 0.07033\n",
      "all done trying2increase usage of unit 923 final usage = 0.91729 124 sec elapsed 8 87 complete, failed patches, unstarted= 74\n",
      "current avg and SD of usage are 1.00065 0.07025\n",
      "all done trying2increase usage of unit 1576 final usage = 0.98307 127 sec elapsed 15 58 complete, failed patches, unstarted= 13\n",
      "current avg and SD of usage are 1.00072 0.07001\n",
      "all done trying2increase usage of unit 68 final usage = 0.98044 128 sec elapsed 16 132 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00077 0.06959\n",
      "begin usage increase for unit 3429 with usage 0.84047 . Sec, total UU units tried = 129 60\n",
      "all done trying2increase usage of unit 3429 final usage = 0.99172 130 sec elapsed 16 9 complete, failed patches, unstarted= 3\n",
      "current avg and SD of usage are 1.0008 0.0692\n",
      "all done trying2increase usage of unit 1190 final usage = 0.92137 132 sec elapsed 7 105 complete, failed patches, unstarted= 3\n",
      "current avg and SD of usage are 1.00082 0.06892\n",
      "all done trying2increase usage of unit 2751 final usage = 0.98178 140 sec elapsed 11 69 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00084 0.06878\n",
      "all done trying2increase usage of unit 216 final usage = 0.98853 141 sec elapsed 12 27 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00088 0.06802\n",
      "all done trying2increase usage of unit 1679 final usage = 0.98187 142 sec elapsed 12 30 complete, failed patches, unstarted= 7\n",
      "current avg and SD of usage are 1.00088 0.06779\n",
      "all done trying2increase usage of unit 1064 final usage = 0.98905 144 sec elapsed 14 35 complete, failed patches, unstarted= 8\n",
      "current avg and SD of usage are 1.00093 0.06756\n",
      "all done trying2increase usage of unit 759 final usage = 0.98573 147 sec elapsed 14 56 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00095 0.0673\n",
      "all done trying2increase usage of unit 379 final usage = 0.98285 148 sec elapsed 15 8 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00096 0.06709\n",
      "all done trying2increase usage of unit 1503 final usage = 0.84907 149 sec elapsed 0 76 complete, failed patches, unstarted= 35\n",
      "current avg and SD of usage are 1.00096 0.06709\n",
      "all done trying2increase usage of unit 915 final usage = 0.8868 152 sec elapsed 5 149 complete, failed patches, unstarted= 41\n",
      "current avg and SD of usage are 1.00099 0.06705\n",
      "begin usage increase for unit 1195 with usage 0.85115 . Sec, total UU units tried = 152 70\n",
      "all done trying2increase usage of unit 1195 final usage = 0.99918 155 sec elapsed 11 33 complete, failed patches, unstarted= 12\n",
      "current avg and SD of usage are 1.00109 0.06689\n",
      "all done trying2increase usage of unit 3363 final usage = 0.98453 160 sec elapsed 11 32 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.0011 0.06614\n",
      "all done trying2increase usage of unit 480 final usage = 0.98672 160 sec elapsed 12 16 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00113 0.06612\n",
      "all done trying2increase usage of unit 2011 final usage = 0.98643 162 sec elapsed 11 20 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00116 0.06572\n",
      "all done trying2increase usage of unit 2224 final usage = 0.98689 164 sec elapsed 12 3 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00117 0.06554\n",
      "all done trying2increase usage of unit 859 final usage = 0.95831 166 sec elapsed 12 29 complete, failed patches, unstarted= 13\n",
      "current avg and SD of usage are 1.00123 0.06539\n",
      "all done trying2increase usage of unit 2393 final usage = 0.98729 167 sec elapsed 12 19 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00126 0.06504\n",
      "all done trying2increase usage of unit 1775 final usage = 0.85454 174 sec elapsed 0 151 complete, failed patches, unstarted= 14\n",
      "current avg and SD of usage are 1.00126 0.06504\n",
      "all done trying2increase usage of unit 3439 final usage = 0.98156 174 sec elapsed 10 15 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00125 0.06498\n",
      "all done trying2increase usage of unit 677 final usage = 0.9812 177 sec elapsed 12 31 complete, failed patches, unstarted= 23\n",
      "current avg and SD of usage are 1.00129 0.06492\n",
      "begin usage increase for unit 53 with usage 0.85636 . Sec, total UU units tried = 177 80\n",
      "all done trying2increase usage of unit 53 final usage = 0.85636 178 sec elapsed 0 16 complete, failed patches, unstarted= 9\n",
      "current avg and SD of usage are 1.00129 0.06492\n",
      "all done trying2increase usage of unit 1174 final usage = 0.98827 180 sec elapsed 11 41 complete, failed patches, unstarted= 5\n",
      "current avg and SD of usage are 1.00131 0.06464\n",
      "all done trying2increase usage of unit 3352 final usage = 0.85849 180 sec elapsed 0 16 complete, failed patches, unstarted= 9\n",
      "current avg and SD of usage are 1.00131 0.06464\n",
      "all done trying2increase usage of unit 2812 final usage = 0.98359 183 sec elapsed 11 19 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00127 0.06393\n",
      "all done trying2increase usage of unit 811 final usage = 0.98274 187 sec elapsed 20 48 complete, failed patches, unstarted= 15\n",
      "current avg and SD of usage are 1.00133 0.06378\n",
      "all done trying2increase usage of unit 599 final usage = 0.98156 188 sec elapsed 10 4 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00132 0.06348\n",
      "all done trying2increase usage of unit 1726 final usage = 0.86125 189 sec elapsed 0 29 complete, failed patches, unstarted= 13\n",
      "current avg and SD of usage are 1.00132 0.06348\n",
      "all done trying2increase usage of unit 1779 final usage = 0.98594 190 sec elapsed 10 5 complete, failed patches, unstarted= 14\n",
      "current avg and SD of usage are 1.00136 0.0633\n",
      "all done trying2increase usage of unit 1134 final usage = 0.87685 192 sec elapsed 1 18 complete, failed patches, unstarted= 29\n",
      "current avg and SD of usage are 1.00137 0.06328\n",
      "all done trying2increase usage of unit 275 final usage = 0.88097 193 sec elapsed 2 18 complete, failed patches, unstarted= 15\n",
      "current avg and SD of usage are 1.00137 0.06323\n",
      "begin usage increase for unit 1041 with usage 0.86394 . Sec, total UU units tried = 193 90\n",
      "all done trying2increase usage of unit 1041 final usage = 0.98038 194 sec elapsed 7 30 complete, failed patches, unstarted= 3\n",
      "current avg and SD of usage are 1.00139 0.06316\n",
      "all done trying2increase usage of unit 95 final usage = 0.95578 199 sec elapsed 8 54 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.0014 0.06302\n",
      "all done trying2increase usage of unit 1388 final usage = 0.98861 204 sec elapsed 11 42 complete, failed patches, unstarted= 16\n",
      "current avg and SD of usage are 1.00144 0.06283\n",
      "all done trying2increase usage of unit 347 final usage = 0.88943 208 sec elapsed 3 115 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00144 0.06279\n",
      "all done trying2increase usage of unit 1034 final usage = 0.98261 209 sec elapsed 13 8 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00147 0.06268\n",
      "all done trying2increase usage of unit 459 final usage = 0.86585 210 sec elapsed 0 22 complete, failed patches, unstarted= 9\n",
      "current avg and SD of usage are 1.00147 0.06268\n",
      "all done trying2increase usage of unit 1416 final usage = 0.88935 211 sec elapsed 2 131 complete, failed patches, unstarted= 24\n",
      "current avg and SD of usage are 1.00149 0.06264\n",
      "all done trying2increase usage of unit 435 final usage = 0.98996 214 sec elapsed 11 55 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00152 0.06196\n",
      "all done trying2increase usage of unit 1751 final usage = 0.98098 215 sec elapsed 10 11 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00155 0.0619\n",
      "all done trying2increase usage of unit 1047 final usage = 0.89181 219 sec elapsed 2 112 complete, failed patches, unstarted= 11\n",
      "current avg and SD of usage are 1.00156 0.06184\n",
      "begin usage increase for unit 1089 with usage 0.86846 . Sec, total UU units tried = 219 100\n",
      "all done trying2increase usage of unit 1089 final usage = 0.98047 220 sec elapsed 14 28 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00158 0.06181\n",
      "all done trying2increase usage of unit 922 final usage = 0.87805 222 sec elapsed 1 156 complete, failed patches, unstarted= 5\n",
      "current avg and SD of usage are 1.00159 0.06179\n",
      "all done trying2increase usage of unit 2660 final usage = 0.98453 224 sec elapsed 12 9 complete, failed patches, unstarted= 4\n",
      "current avg and SD of usage are 1.0016 0.06158\n",
      "all done trying2increase usage of unit 1227 final usage = 0.90186 228 sec elapsed 3 67 complete, failed patches, unstarted= 9\n",
      "current avg and SD of usage are 1.00162 0.06151\n",
      "all done trying2increase usage of unit 1498 final usage = 0.98208 229 sec elapsed 10 50 complete, failed patches, unstarted= 4\n",
      "current avg and SD of usage are 1.00164 0.0614\n",
      "all done trying2increase usage of unit 1381 final usage = 0.98312 231 sec elapsed 13 18 complete, failed patches, unstarted= 18\n",
      "current avg and SD of usage are 1.00171 0.06131\n",
      "all done trying2increase usage of unit 737 final usage = 0.98924 232 sec elapsed 10 23 complete, failed patches, unstarted= 3\n",
      "current avg and SD of usage are 1.00169 0.06092\n",
      "all done trying2increase usage of unit 527 final usage = 0.98197 234 sec elapsed 11 13 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.0017 0.06081\n",
      "all done trying2increase usage of unit 67 final usage = 0.98147 234 sec elapsed 9 32 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.0017 0.06072\n",
      "all done trying2increase usage of unit 1465 final usage = 0.90064 235 sec elapsed 3 18 complete, failed patches, unstarted= 12\n",
      "current avg and SD of usage are 1.00172 0.06063\n",
      "begin usage increase for unit 1152 with usage 0.8741 . Sec, total UU units tried = 235 110\n",
      "all done trying2increase usage of unit 1152 final usage = 0.88211 236 sec elapsed 1 22 complete, failed patches, unstarted= 33\n",
      "current avg and SD of usage are 1.00173 0.06061\n",
      "all done trying2increase usage of unit 403 final usage = 0.88922 241 sec elapsed 1 80 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00172 0.0606\n",
      "all done trying2increase usage of unit 3252 final usage = 0.98896 243 sec elapsed 9 2 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00174 0.06027\n",
      "all done trying2increase usage of unit 953 final usage = 0.9952 244 sec elapsed 9 4 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00173 0.05996\n",
      "all done trying2increase usage of unit 22 final usage = 0.94368 249 sec elapsed 5 104 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00178 0.05984\n",
      "all done trying2increase usage of unit 55 final usage = 0.87691 250 sec elapsed 0 16 complete, failed patches, unstarted= 5\n",
      "current avg and SD of usage are 1.00178 0.05984\n",
      "all done trying2increase usage of unit 1286 final usage = 0.98735 250 sec elapsed 7 14 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.0018 0.05976\n",
      "all done trying2increase usage of unit 370 final usage = 0.98854 251 sec elapsed 8 47 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.0018 0.05954\n",
      "all done trying2increase usage of unit 1831 final usage = 0.88545 254 sec elapsed 1 123 complete, failed patches, unstarted= 11\n",
      "current avg and SD of usage are 1.00181 0.05953\n",
      "all done trying2increase usage of unit 121 final usage = 0.98205 257 sec elapsed 11 63 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00183 0.05927\n",
      "begin usage increase for unit 1076 with usage 0.87825 . Sec, total UU units tried = 257 120\n",
      "all done trying2increase usage of unit 1076 final usage = 0.98561 260 sec elapsed 6 19 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00188 0.05918\n",
      "all done trying2increase usage of unit 1588 final usage = 0.88741 261 sec elapsed 1 30 complete, failed patches, unstarted= 17\n",
      "current avg and SD of usage are 1.00189 0.05916\n",
      "all done trying2increase usage of unit 3408 final usage = 0.98075 265 sec elapsed 9 27 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00195 0.05903\n",
      "all done trying2increase usage of unit 2431 final usage = 0.99188 266 sec elapsed 8 4 complete, failed patches, unstarted= 10\n",
      "current avg and SD of usage are 1.00197 0.0589\n",
      "all done trying2increase usage of unit 1331 final usage = 0.91548 268 sec elapsed 3 103 complete, failed patches, unstarted= 7\n",
      "current avg and SD of usage are 1.00197 0.05884\n",
      "all done trying2increase usage of unit 492 final usage = 0.87933 270 sec elapsed 0 131 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00197 0.05884\n",
      "all done trying2increase usage of unit 3115 final usage = 0.98143 271 sec elapsed 8 7 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00199 0.05855\n",
      "all done trying2increase usage of unit 483 final usage = 0.98085 273 sec elapsed 9 21 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00203 0.05845\n",
      "all done trying2increase usage of unit 657 final usage = 0.88303 275 sec elapsed 0 174 complete, failed patches, unstarted= 4\n",
      "current avg and SD of usage are 1.00203 0.05845\n",
      "all done trying2increase usage of unit 2577 final usage = 0.9853 278 sec elapsed 11 14 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00206 0.05833\n",
      "begin usage increase for unit 938 with usage 0.88476 . Sec, total UU units tried = 278 130\n",
      "all done trying2increase usage of unit 938 final usage = 0.88476 280 sec elapsed 0 39 complete, failed patches, unstarted= 14\n",
      "current avg and SD of usage are 1.00206 0.05833\n",
      "all done trying2increase usage of unit 2919 final usage = 0.98902 281 sec elapsed 8 5 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00209 0.05812\n",
      "all done trying2increase usage of unit 719 final usage = 0.88578 283 sec elapsed 0 171 complete, failed patches, unstarted= 9\n",
      "current avg and SD of usage are 1.00209 0.05812\n",
      "all done trying2increase usage of unit 555 final usage = 0.98206 284 sec elapsed 8 22 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00212 0.0581\n",
      "all done trying2increase usage of unit 2270 final usage = 0.98359 286 sec elapsed 9 14 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00215 0.05801\n",
      "all done trying2increase usage of unit 1330 final usage = 0.98109 288 sec elapsed 7 95 complete, failed patches, unstarted= 8\n",
      "current avg and SD of usage are 1.00219 0.05792\n",
      "all done trying2increase usage of unit 145 final usage = 0.99013 289 sec elapsed 11 40 complete, failed patches, unstarted= 13\n",
      "current avg and SD of usage are 1.00221 0.05767\n",
      "all done trying2increase usage of unit 1137 final usage = 0.98257 294 sec elapsed 9 59 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00225 0.05749\n",
      "all done trying2increase usage of unit 587 final usage = 0.98891 303 sec elapsed 11 93 complete, failed patches, unstarted= 9\n",
      "current avg and SD of usage are 1.0023 0.05743\n",
      "all done trying2increase usage of unit 2324 final usage = 0.9893 304 sec elapsed 7 3 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00231 0.05719\n",
      "begin usage increase for unit 1427 with usage 0.88949 . Sec, total UU units tried = 304 140\n",
      "all done trying2increase usage of unit 1427 final usage = 0.88949 305 sec elapsed 0 47 complete, failed patches, unstarted= 20\n",
      "current avg and SD of usage are 1.00231 0.05719\n",
      "all done trying2increase usage of unit 4 final usage = 0.9875 307 sec elapsed 10 28 complete, failed patches, unstarted= 4\n",
      "current avg and SD of usage are 1.00235 0.05704\n",
      "all done trying2increase usage of unit 1324 final usage = 0.98351 309 sec elapsed 9 38 complete, failed patches, unstarted= 5\n",
      "current avg and SD of usage are 1.00237 0.05696\n",
      "all done trying2increase usage of unit 1743 final usage = 0.98185 310 sec elapsed 8 1 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00238 0.05682\n",
      "all done trying2increase usage of unit 187 final usage = 0.9873 312 sec elapsed 9 35 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00239 0.0568\n",
      "all done trying2increase usage of unit 171 final usage = 0.97009 317 sec elapsed 5 81 complete, failed patches, unstarted= 2\n",
      "current avg and SD of usage are 1.00245 0.05675\n",
      "all done trying2increase usage of unit 869 final usage = 0.93479 318 sec elapsed 3 32 complete, failed patches, unstarted= 13\n",
      "current avg and SD of usage are 1.00242 0.05611\n",
      "all done trying2increase usage of unit 113 final usage = 0.98462 322 sec elapsed 9 73 complete, failed patches, unstarted= 5\n",
      "current avg and SD of usage are 1.00244 0.05605\n",
      "all done trying2increase usage of unit 1201 final usage = 0.89515 323 sec elapsed 0 27 complete, failed patches, unstarted= 14\n",
      "current avg and SD of usage are 1.00244 0.05605\n",
      "all done trying2increase usage of unit 213 final usage = 0.89528 324 sec elapsed 0 23 complete, failed patches, unstarted= 3\n",
      "current avg and SD of usage are 1.00244 0.05605\n",
      "begin usage increase for unit 827 with usage 0.89548 . Sec, total UU units tried = 324 150\n",
      "all done trying2increase usage of unit 827 final usage = 0.96534 326 sec elapsed 6 16 complete, failed patches, unstarted= 15\n",
      "current avg and SD of usage are 1.00245 0.05595\n",
      "all done trying2increase usage of unit 486 final usage = 0.89564 327 sec elapsed 0 99 complete, failed patches, unstarted= 25\n",
      "current avg and SD of usage are 1.00245 0.05595\n",
      "all done trying2increase usage of unit 98 final usage = 0.92396 334 sec elapsed 3 87 complete, failed patches, unstarted= 15\n",
      "current avg and SD of usage are 1.00247 0.05593\n",
      "all done trying2increase usage of unit 320 final usage = 0.89658 335 sec elapsed 0 79 complete, failed patches, unstarted= 34\n",
      "current avg and SD of usage are 1.00247 0.05593\n",
      "all done trying2increase usage of unit 1051 final usage = 0.98016 336 sec elapsed 7 98 complete, failed patches, unstarted= 12\n",
      "current avg and SD of usage are 1.00251 0.0558\n",
      "all done trying2increase usage of unit 1930 final usage = 0.98821 337 sec elapsed 4 7 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.0025 0.05568\n",
      "all done trying2increase usage of unit 1772 final usage = 0.90758 340 sec elapsed 1 160 complete, failed patches, unstarted= 4\n",
      "current avg and SD of usage are 1.0025 0.05566\n",
      "all done trying2increase usage of unit 2663 final usage = 0.98511 344 sec elapsed 8 10 complete, failed patches, unstarted= 3\n",
      "current avg and SD of usage are 1.00254 0.05557\n",
      "all done trying2increase usage of unit 342 final usage = 0.98794 346 sec elapsed 7 196 complete, failed patches, unstarted= 29\n",
      "current avg and SD of usage are 1.00254 0.05523\n",
      "all done trying2increase usage of unit 319 final usage = 0.89748 349 sec elapsed 0 87 complete, failed patches, unstarted= 0\n",
      "current avg and SD of usage are 1.00254 0.05523\n",
      "begin usage increase for unit 78 with usage 0.89758 . Sec, total UU units tried = 349 160\n",
      "all done trying2increase usage of unit 78 final usage = 0.98274 351 sec elapsed 8 68 complete, failed patches, unstarted= 3\n",
      "current avg and SD of usage are 1.00256 0.05517\n",
      "all done trying2increase usage of unit 2712 final usage = 0.98751 361 sec elapsed 11 17 complete, failed patches, unstarted= 1\n",
      "current avg and SD of usage are 1.00256 0.05495\n"
     ]
    }
   ],
   "source": [
    "print(\"For now, we will freeze the HDs with split units prior to patching.\")\n",
    "print(\"Start with underpatching. This algorithm simplified vs. vanillaHD to manage blockiness.\")\n",
    "\n",
    "maxSD = 0.055  #0.07  #0.05   #adjust down if distro already tight\n",
    "print(\"Currently, we will stop patching when the overall sd of usage is less than\",maxSD)\n",
    "maxSD = float(input(\"enter updated maxSD value\"))\n",
    "stopMinUse = 1. - maxSD\n",
    "#print(\"we will stop patching on individual underused units when their usage exceeds\",r5(stopMinUse))\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        maxNtries +=1\n",
    "print(\"this would currently cover a total of\",maxNtries,\"units\")\n",
    "maxNtries = int(input(\"enter updated number of units to try boosting usage\"))\n",
    "stopMinUse = 0.98 #float(input(\"enter updated stopMinUse value for ending usage boost on a unit; I reco 0.98\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage below\",stopMinUse)\n",
    "maxExchangePop = 0.25*aDP #this is widened vs. vanillaHD to overcome blockiness\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "debug1 = 10 #int(input(\"enter 1 to print out stats for every patched HD, otherwise enter reporting frequency\"))\n",
    "print(\"Let's further tighten the distro with exchanges up to\",int(maxExchangePop),\"= aDP*\",r3(maxExchangePop/aDP) ) \n",
    "maxGap = aDP - minDistrictPop #0.9 * np.median(unitPop) \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "nonfrozenList = list()\n",
    "for t in popHDlist:\n",
    "    if hasSplitUnit[t] != 1:  #don't mess with the small number of HDs that have to have a split muni\n",
    "        nonfrozenList.append(t)\n",
    "\n",
    "attemptedSmallUs, startTime = list(), time.time()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries:\n",
    "    #simplified vs. vanillaHD - always work on the lowest-used unit.\n",
    "    eligUnitUse = unitUse.copy()\n",
    "    for u in range(nUnits):\n",
    "        if u in attemptedSmallUs: #we already tried this one, so lock it out\n",
    "            eligUnitUse[u] = 999.  #preventing re-selection\n",
    "    UUU = eligUnitUse.index(np.min(eligUnitUse))\n",
    "    attemptedSmallUs.append(UUU)\n",
    "    UUUc = [UUU] + unitNbrs[UUU]\n",
    "    if len(attemptedSmallUs) % debug1 == 0:\n",
    "        print(\"begin usage increase for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Sec, total UU units tried =\",\n",
    "              int(time.time()-startTime),len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1.:\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists, UUUcSet = list(), list(), set(UUUc)\n",
    "    for t in nonfrozenList: #popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUcSet) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "        idx0 = np.argsort(uuuDists)\n",
    "    hasCandidates = True\n",
    "    if len(uuuDists) == 0:  #this underused unit is buried inside others; skip it\n",
    "        hasCandidates = False\n",
    "        print(\"   Couldn't find any HDs adjacent to underused unit\",UUU)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs) and hasCandidates: #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 40 == 0 and debug1 == 1:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(UUUcSet)\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not (contig and complementContig): #we can't add whole cluster; neighbors may be enclavy.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "            loopUUUc = [UUU]\n",
    "        if contig and complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in uuCandidates:\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    cContig = wontEnclave(addU, list(trySet), unitNbrs, borderUnits)  #4/20/24 sub this in as faster? vs below line\n",
    "                    #contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\n",
    "                    if cContig: #contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap and u != homeU[t]:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if contig and cContig:\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates + [homeU[t]]:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            currPop = np.sum([ unitPop[u] for u in trySet] )\n",
    "            if abs(currPop - aDP) <= maxGap: \n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying2increase usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"complete, failed patches, unstarted=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "6f7f2f60-aa6c-4d46-b2e3-7d2f68841e68",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kqV+/fvr22281f/58paWlKSoqSpJUXFys6Ohox3rFxcUaMGCAJCkqKkolJSVO262vr9fx48cd6/9cUFCQgoKCXP12AACAB3L5EZiTJ0/K19d5s35+fmpsbJQkxcfHKyoqSjk5OY7lFRUVysvLU2JioiQpMTFRZWVlys/Pd9Rs3bpVjY2NSkhIcHXLAADAMC4/AjNmzBg9++yz6tatmy6//HJ98skneumll3TfffdJknx8fJSRkaF58+apV69eio+PV1ZWlmJiYnTrrbdKkvr06aNRo0bp/vvv18qVK1VXV6f09HSNHz+eK5AAAIDrA8zSpUuVlZWl3/3udyopKVFMTIweeOABzZw501EzdepUVVVVafLkySorK9Pw4cO1adMmBQcHO2pee+01paena+TIkfL19dXYsWO1ZMkSV7cLAAAM5GP99Ba5XqSiokJhYWEqLy9XaGhoe7cDwIU+LyzXzUt3auPDw3VFbNh51wDwPC39/OZZSAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHJc/CwkAfqnCsmqVVtU2ufxQSaUbuwHgiQgwADxKYVm1kl/cruq6hmbrbAF+6hwS6KauAHgaAgwAj1JaVavqugZljxugnpEdm6zrHBKo2HCbGzsD4EkIMAA8Us/IjjxFGkCTOIkXAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYp00CTGFhoe666y516dJFNptN/fr100cffeRYblmWZs6cqejoaNlsNiUnJ+urr75y2sbx48eVmpqq0NBQhYeHa+LEiaqsrGyLdgEAgGFcHmBKS0s1bNgwBQQE6B//+If279+vF198UZ07d3bULFiwQEuWLNHKlSuVl5enkJAQpaSk6NSpU46a1NRU7du3T5s3b9bGjRu1Y8cOTZ482dXtAgAAA/m7eoMvvPCC4uLitHr1ase8+Ph4x8+WZSk7O1szZszQLbfcIkl69dVXZbfbtWHDBo0fP14HDhzQpk2b9OGHH2rQoEGSpKVLl+qmm27SwoULFRMT4+q2AQCAQVx+BObdd9/VoEGD9Jvf/EaRkZEaOHCg/vSnPzmWHz58WEVFRUpOTnbMCwsLU0JCgnJzcyVJubm5Cg8Pd4QXSUpOTpavr6/y8vLOut+amhpVVFQ4TQAAwDu5PMB8/fXXevnll9WrVy/985//1EMPPaRHHnlEa9eulSQVFRVJkux2u9N6drvdsayoqEiRkZFOy/39/RUREeGo+bn58+crLCzMMcXFxbn6rQEAAA/h8gDT2Nioq666Ss8995wGDhyoyZMn6/7779fKlStdvSsn06dPV3l5uWM6evRom+4PAAC0H5cHmOjoaPXt29dpXp8+fXTkyBFJUlRUlCSpuLjYqaa4uNixLCoqSiUlJU7L6+vrdfz4cUfNzwUFBSk0NNRpAgAA3snlAWbYsGE6ePCg07wvv/xS3bt3l/TjCb1RUVHKyclxLK+oqFBeXp4SExMlSYmJiSorK1N+fr6jZuvWrWpsbFRCQoKrWwYAAIZx+VVIjz32mK655ho999xz+u1vf6s9e/bolVde0SuvvCJJ8vHxUUZGhubNm6devXopPj5eWVlZiomJ0a233irpxyM2o0aNcnz1VFdXp/T0dI0fP54rkAAAgOsDzODBg/XOO+9o+vTpmjNnjuLj45Wdna3U1FRHzdSpU1VVVaXJkyerrKxMw4cP16ZNmxQcHOyoee2115Senq6RI0fK19dXY8eO1ZIlS1zdLgAAMJDLA4wk3Xzzzbr55pubXO7j46M5c+Zozpw5TdZERERo3bp1bdEeAAAwHM9CAgAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADBOmweY559/Xj4+PsrIyHDMO3XqlKZMmaIuXbqoY8eOGjt2rIqLi53WO3LkiEaPHq0OHTooMjJSTz75pOrr69u6XQAAYIA2DTAffvih/vjHP+rKK690mv/YY4/pb3/7m9566y1t375d3333nW6//XbH8oaGBo0ePVq1tbXatWuX1q5dqzVr1mjmzJlt2S4AADCEf1ttuLKyUqmpqfrTn/6kefPmOeaXl5dr1apVWrdunW644QZJ0urVq9WnTx/t3r1bQ4cO1fvvv6/9+/dry5YtstvtGjBggObOnaunnnpKs2bNUmBgYFu1DcDLHCqpbHZ555BAxYbb3NQNAFdpswAzZcoUjR49WsnJyU4BJj8/X3V1dUpOTnbM6927t7p166bc3FwNHTpUubm56tevn+x2u6MmJSVFDz30kPbt26eBAwe2VdsAvETnkEDZAvyUsb6g2TpbgJ+2PJ5EiAEM0yYB5o033tDHH3+sDz/88IxlRUVFCgwMVHh4uNN8u92uoqIiR81Pw8vp5aeXnU1NTY1qamocrysqKn7JWwBguNhwm7Y8nqTSqtomaw6VVCpjfYFKq2oJMIBhXB5gjh49qkcffVSbN29WcHCwqzffpPnz52v27Nlu2x8AzxcbbiOYAF7K5Sfx5ufnq6SkRFdddZX8/f3l7++v7du3a8mSJfL395fdbldtba3Kysqc1isuLlZUVJQkKSoq6oyrkk6/Pl3zc9OnT1d5ebljOnr0qKvfGgAA8BAuDzAjR47U3r17VVBQ4JgGDRqk1NRUx88BAQHKyclxrHPw4EEdOXJEiYmJkqTExETt3btXJSUljprNmzcrNDRUffv2Pet+g4KCFBoa6jQBAADv5PKvkDp16qQrrrjCaV5ISIi6dOnimD9x4kRlZmYqIiJCoaGhevjhh5WYmKihQ4dKkm688Ub17dtXd999txYsWKCioiLNmDFDU6ZMUVBQkKtbBgAAhmmzq5Cas2jRIvn6+mrs2LGqqalRSkqKVqxY4Vju5+enjRs36qGHHlJiYqJCQkKUlpamOXPmtEe7AADAw7glwGzbts3pdXBwsJYvX67ly5c3uU737t313nvvtXFnAADARDwLCQAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxvFv7wYAXFgKy6pVWlXb5PJDJZVu7AaAqQgwANymsKxayS9uV3VdQ7N1tgA/dQ4JdFNXAExEgAHgNqVVtaqua1D2uAHqGdmxybrOIYGKDbe5sTMApiHAAHC7npEddUVsWHu3AcBgnMQLAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwjn97NwDAexSWVau0qrbJ5YdKKt3YDQBvRoAB4BKFZdVKfnG7qusamq2zBfipc0igm7oC4K0IMABcorSqVtV1DcoeN0A9Izs2Wdc5JFCx4TY3dgbAGxFgALhUz8iOuiI2rL3bAODlOIkXAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxXB5g5s+fr8GDB6tTp06KjIzUrbfeqoMHDzrVnDp1SlOmTFGXLl3UsWNHjR07VsXFxU41R44c0ejRo9WhQwdFRkbqySefVH19vavbBQAABnJ5gNm+fbumTJmi3bt3a/Pmzaqrq9ONN96oqqoqR81jjz2mv/3tb3rrrbe0fft2fffdd7r99tsdyxsaGjR69GjV1tZq165dWrt2rdasWaOZM2e6ul0AAGAgl98HZtOmTU6v16xZo8jISOXn5+u6665TeXm5Vq1apXXr1umGG26QJK1evVp9+vTR7t27NXToUL3//vvav3+/tmzZIrvdrgEDBmju3Ll66qmnNGvWLAUGchdPAAAuZG1+I7vy8nJJUkREhCQpPz9fdXV1Sk5OdtT07t1b3bp1U25uroYOHarc3Fz169dPdrvdUZOSkqKHHnpI+/bt08CBA8/YT01NjWpqahyvKyoq2uotARcknnMEwJO0aYBpbGxURkaGhg0bpiuuuEKSVFRUpMDAQIWHhzvV2u12FRUVOWp+Gl5OLz+97Gzmz5+v2bNnu/gdAJB4zhEAz9OmAWbKlCn6/PPPtXPnzrbcjSRp+vTpyszMdLyuqKhQXFxcm+8XuBDwnCMAnqbNAkx6ero2btyoHTt26OKLL3bMj4qKUm1trcrKypyOwhQXFysqKspRs2fPHqftnb5K6XTNzwUFBSkoKMjF7wLAT/GcIwCewuVXIVmWpfT0dL3zzjvaunWr4uPjnZZfffXVCggIUE5OjmPewYMHdeTIESUmJkqSEhMTtXfvXpWUlDhqNm/erNDQUPXt29fVLQMAAMO4/AjMlClTtG7dOv31r39Vp06dHOeshIWFyWazKSwsTBMnTlRmZqYiIiIUGhqqhx9+WImJiRo6dKgk6cYbb1Tfvn119913a8GCBSoqKtKMGTM0ZcoUjrIAAADXB5iXX35ZknT99dc7zV+9erXuvfdeSdKiRYvk6+ursWPHqqamRikpKVqxYoWj1s/PTxs3btRDDz2kxMREhYSEKC0tTXPmzHF1uwAAwEAuDzCWZZ2zJjg4WMuXL9fy5cubrOnevbvee+89V7YGAAC8BM9CAgAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHH827sBAO2vsKxapVW1TS4/VFLpxm4A4NwIMMAFrrCsWskvbld1XUOzdbYAP3UOCXRTVwDQPAIMcIErrapVdV2DsscNUM/Ijk3WdQ4JVGy4zY2dAUDTCDAAJEk9Izvqitiw9m4DAFqEk3gBAIBxCDAAAMA4BBgAAGAczoEBcME712XinMAMeB4CDIALVueQQNkC/JSxvqDZOluAn7Y8nkSIATwIAQbwctykrmmx4TZteTzpnOOTsb5ApVW1BBjAgxBgAC/GTerOLTbcRjABDESAAbwYN6kD4K0IMMAFgJvUAfA2XEYNAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOPwLCTAYIVl1Sqtqm1y+aGSSjd2AwDuQ4ABDFVYVq3kF7eruq6h2TpbgJ86hwS6qSsAcA8CDGCo0qpaVdc1KHvcAPWM7NhkXeeQQMWG29zYGQC0PQIMYLiekR11RWxYe7fh9c71dRxBEXAvAgwANKNzSKBsAX7KWF/QbJ0twE9bHk8ixABuQoABgGbEhtu05fGkc54snbG+QKVVtQQYwE0IMABwDrHhNoIJ4GG4DwwAADAOAQYAABiHr5AAD8VN6gCgaQQYwANxkzoAaB4BBvBA3KQOAJpHgAE8GDepA4Cz4yReAABgHAIMAAAwDgEGAAAYhwADAACMw0m8QDvgHi/eiSdWA+5DgAHcjHu8eJ/WPLF65d1Xq0szv1dCDtAyBBjAzbjHi/dpyROrf6iq1YN/zlfa/7en2W3ZAvy05fEkfvfAOXh0gFm+fLn+8Ic/qKioSP3799fSpUs1ZMiQ9m4LcAnu8eJdWvLE6nOFnEMllcpYX6DSqloCDHAOHhtg1q9fr8zMTK1cuVIJCQnKzs5WSkqKDh48qMjIyPZuD2gS57egKS0JOZJ559Kc629e8ryeYT4fy7Ks9m7ibBISEjR48GAtW7ZMktTY2Ki4uDg9/PDDmjZt2jnXr6ioUFhYmMrLyxUaGtrW7QKSWnd+C18T4Odc+ffTklDREucKHvzNw9Va+vntkUdgamtrlZ+fr+nTpzvm+fr6Kjk5Wbm5uWddp6amRjU1NY7X5eXlkn4cCFc7VnFKxyprzl2IC87Xx6pUVXlCz9/eT5d2DWmyLrxDoDr51qmios6N3cHTdfKV3rl/oMpONh08vj5WpWlv79X2vd82+Td2/GSdMt74RKfqGn9xT8EBvsoeP1ARHQKa7Odcf/Mt6Rnm6doxSF1Dg12+3dOf2+c8vmJ5oMLCQkuStWvXLqf5Tz75pDVkyJCzrvPMM89YkpiYmJiYmJi8YDp69GizWcEjj8Ccj+nTpyszM9PxurGxUcePH1eXLl3k4+PTpvuuqKhQXFycjh49ytdV58BYtQzj1HKMVcsxVi3DOLVcW4yVZVk6ceKEYmJimq3zyABz0UUXyc/PT8XFxU7zi4uLFRUVddZ1goKCFBQU5DQvPDy8rVo8q9DQUP7YW4ixahnGqeUYq5ZjrFqGcWo5V49VWFjYOWs88lECgYGBuvrqq5WTk+OY19jYqJycHCUmJrZjZwAAwBN45BEYScrMzFRaWpoGDRqkIUOGKDs7W1VVVZowYUJ7twYAANqZxwaYcePG6dixY5o5c6aKioo0YMAAbdq0SXa7vb1bO0NQUJCeeeaZM77CwpkYq5ZhnFqOsWo5xqplGKeWa8+x8tj7wAAAADTFI8+BAQAAaA4BBgAAGIcAAwAAjEOAAQAAxiHAtNDy5ct1ySWXKDg4WAkJCdqzZ0+Ttddff718fHzOmEaPHu3GjttPa8ZKkrKzs3XZZZfJZrMpLi5Ojz32mE6dOuWmbttPa8aprq5Oc+bMUY8ePRQcHKz+/ftr06ZNbuy2/ezYsUNjxoxRTEyMfHx8tGHDhnOus23bNl111VUKCgpSz549tWbNmjbvs721dpy+//573XnnnfrVr34lX19fZWRkuKVPT9DasXr77bf161//Wl27dlVoaKgSExP1z3/+0z3NtqPWjtPOnTs1bNgwdenSRTabTb1799aiRYvarD8CTAusX79emZmZeuaZZ/Txxx+rf//+SklJUUlJyVnr3377bX3//feO6fPPP5efn59+85vfuLlz92vtWK1bt07Tpk3TM888owMHDmjVqlVav369fv/737u5c/dq7TjNmDFDf/zjH7V06VLt379fDz74oG677TZ98sknbu7c/aqqqtS/f38tX768RfWHDx/W6NGjNWLECBUUFCgjI0OTJk3y+g+c1o5TTU2NunbtqhkzZqh///5t3J1nae1Y7dixQ7/+9a/13nvvKT8/XyNGjNCYMWO8/t9fa8cpJCRE6enp2rFjhw4cOKAZM2ZoxowZeuWVV9qmQdc8ftG7DRkyxJoyZYrjdUNDgxUTE2PNnz+/ResvWrTI6tSpk1VZWdlWLXqM1o7VlClTrBtuuMFpXmZmpjVs2LA27bO9tXacoqOjrWXLljnNu/32263U1NQ27dPTSLLeeeedZmumTp1qXX755U7zxo0bZ6WkpLRhZ56lJeP0U0lJSdajjz7aZv14staO1Wl9+/a1Zs+e7fqGPNT5jtNtt91m3XXXXa5vyLIsjsCcQ21trfLz85WcnOyY5+vrq+TkZOXm5rZoG6tWrdL48eMVEuLdj5E/n7G65pprlJ+f7/j65Ouvv9Z7772nm266yS09t4fzGaeamhoFBzs/tt5ms2nnzp1t2quJcnNzncZWklJSUlr87xU4l8bGRp04cUIRERHt3YpH++STT7Rr1y4lJSW1yfY99k68nuLf//63GhoazrgDsN1u1xdffHHO9ffs2aPPP/9cq1ataqsWPcb5jNWdd96pf//73xo+fLgsy1J9fb0efPBBr/4K6XzGKSUlRS+99JKuu+469ejRQzk5OXr77bfV0NDgjpaNUlRUdNaxraioUHV1tWw2Wzt1Bm+xcOFCVVZW6re//W17t+KRLr74Yh07dkz19fWaNWuWJk2a1Cb74QhMG1u1apX69eunIUOGtHcrHmnbtm167rnntGLFCn388cd6++239fe//11z585t79Y8yuLFi9WrVy/17t1bgYGBSk9P14QJE+Tryz9hwJ3WrVun2bNn680331RkZGR7t+OR/ud//kcfffSRVq5cqezsbL3++uttsh+OwJzDRRddJD8/PxUXFzvNLy4uVlRUVLPrVlVV6Y033tCcOXPaskWPcT5jlZWVpbvvvtuR0Pv166eqqipNnjxZTz/9tFd+QJ/POHXt2lUbNmzQqVOn9MMPPygmJkbTpk3TpZde6o6WjRIVFXXWsQ0NDeXoC36RN954Q5MmTdJbb711xteU+H/i4+Ml/fjf8+LiYs2aNUt33HGHy/fjfZ8OLhYYGKirr75aOTk5jnmNjY3KyclRYmJis+u+9dZbqqmp0V133dXWbXqE8xmrkydPnhFS/Pz8JEmWlz6m65f8TQUHBys2Nlb19fX6y1/+oltuuaWt2zVOYmKi09hK0ubNm885tkBzXn/9dU2YMEGvv/76BXNLDFdobGxUTU1Nm2ybIzAtkJmZqbS0NA0aNEhDhgxRdna2qqqqNGHCBEnSPffco9jYWM2fP99pvVWrVunWW29Vly5d2qPtdtHasRozZoxeeuklDRw4UAkJCTp06JCysrI0ZswYR5DxRq0dp7y8PBUWFmrAgAEqLCzUrFmz1NjYqKlTp7bn23CLyspKHTp0yPH68OHDKigoUEREhLp166bp06ersLBQr776qiTpwQcf1LJlyzR16lTdd9992rp1q9588039/e9/b6+34BatHSdJKigocKx77NgxFRQUKDAwUH379nV3+27V2rFat26d0tLStHjxYiUkJKioqEjSjyfSh4WFtct7cIfWjtPy5cvVrVs39e7dW9KPl58vXLhQjzzySNs02CbXNnmhpUuXWt26dbMCAwOtIUOGWLt373YsS0pKstLS0pzqv/jiC0uS9f7777u50/bXmrGqq6uzZs2aZfXo0cMKDg624uLirN/97ndWaWmp+xt3s9aM07Zt26w+ffpYQUFBVpcuXay7777bKiwsbIeu3e+DDz6wJJ0xnR6ftLQ0Kykp6Yx1BgwYYAUGBlqXXnqptXr1arf37W7nM05nq+/evbvbe3e31o5VUlJSs/XeqrXjtGTJEuvyyy+3OnToYIWGhloDBw60VqxYYTU0NLRJfz6W5aXH6QEAgNfiHBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjPP/A7qKqi2aR/q2AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " patched use avg 1.00338 and SD 0.05503\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 8941\n",
      "working on HD 6400 out of 8941\n",
      "working on HD 4000 out of 8941\n",
      "working on HD 8800 out of 8941\n",
      "working on HD 4800 out of 8941\n",
      "working on HD 1600 out of 8941\n",
      "working on HD 5600 out of 8941\n",
      "working on HD 2400 out of 8941\n",
      "working on HD 800 out of 8941\n",
      "working on HD 8000 out of 8941\n",
      "working on HD 3200 out of 8941\n",
      "working on HD 7200 out of 8941\n",
      "all done checking HD and complement contiguity for all 8941 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    if hasSplitUnit[t] == 1:\n",
    "        unitUse[splitUnitNo[t]] -= (1. - splitUnitFrac[t]) * nDistricts * HDweight[t]\n",
    "#    for u in unpatchedHDlist[t]:\n",
    "#        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "#plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "#unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\" patched use avg\", r5(patchedAvg),\"and SD\",r5(patchedSD) )\n",
    "#print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.axvline(0.95*aDP, ls=\"dotted\")\n",
    "plt.axvline(1.05*aDP, ls=\"dotted\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%800 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "5faa4270-4a8f-4777-b514-6d72cd77718b",
   "metadata": {},
   "outputs": [],
   "source": [
    "underpatchedUnitList = [HDunitList[t].copy() for t in range(nHDs) ] #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "6e54e08e-d07a-418f-b730-7bbc9d336a23",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.04 = default maxSD\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter maxSD 0.04\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "default use threshold for moving on to next overused unit is 1.02\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated stopMaxUse value 1.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 214 units out of 3442 with usage above 1.02\n",
      "maxExchangePop is currently 0.25 fraction of avgDistrictPop\n",
      "this block reduces overuse, with exchanges up to 29796\n",
      "current avg and SD of unit usage are 1.00173 0.05532 . Now trying to reduce up to 214 units' overusage\n",
      "starting to reduce usage for unit 374 with usage 1.29782 . Total units tried = 1\n",
      "try to drop unit 374 from 8 th HD.  usage down to 1.2447231429807872\n",
      "try to drop unit 374 from 16 th HD.  usage down to 1.175562534789646\n",
      "try to drop unit 374 from 24 th HD.  usage down to 1.1257917319521011\n",
      "try to drop unit 374 from 32 th HD.  usage down to 1.0918448896930342\n",
      "try to drop unit 374 from 40 th HD.  usage down to 1.0688137275573248\n",
      "try to drop unit 374 from 48 th HD.  usage down to 1.057109366471964\n",
      "try to drop unit 374 from 56 th HD.  usage down to 1.051462746392786\n",
      "try to drop unit 374 from 64 th HD.  usage down to 1.0245553012309403\n",
      "all done trying to reduce usage of unit 374 final usage = 1.02456 0 sec elapsed 28 28 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 1.00166 0.05037\n",
      "starting to reduce usage for unit 23 with usage 1.23054 . Total units tried = 2\n",
      "try to drop unit 23 from 3 th HD.  usage down to 1.2066567012282492\n",
      "try to drop unit 23 from 6 th HD.  usage down to 1.172223226035197\n",
      "try to drop unit 23 from 9 th HD.  usage down to 1.1470273863654248\n",
      "try to drop unit 23 from 12 th HD.  usage down to 1.1346434172170432\n",
      "try to drop unit 23 from 15 th HD.  usage down to 1.108591774801243\n",
      "try to drop unit 23 from 18 th HD.  usage down to 1.0809627704613909\n",
      "try to drop unit 23 from 21 th HD.  usage down to 1.067278316747967\n",
      "try to drop unit 23 from 24 th HD.  usage down to 1.0437940825702408\n",
      "try to drop unit 23 from 27 th HD.  usage down to 1.0320309899238806\n",
      "all done trying to reduce usage of unit 23 final usage = 1.03203 2 sec elapsed 16 6 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00155 0.04645\n",
      "starting to reduce usage for unit 63 with usage 1.20922 . Total units tried = 3\n",
      "try to drop unit 63 from 7 th HD.  usage down to 1.1259847070809312\n",
      "try to drop unit 63 from 14 th HD.  usage down to 1.0462104667944574\n",
      "all done trying to reduce usage of unit 63 final usage = 1.01017 3 sec elapsed 16 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00143 0.04509\n",
      "starting to reduce usage for unit 90 with usage 1.18548 . Total units tried = 4\n",
      "try to drop unit 90 from 8 th HD.  usage down to 1.0951925886699851\n",
      "all done trying to reduce usage of unit 90 final usage = 1.0138 4 sec elapsed 13 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00133 0.04434\n",
      "starting to reduce usage for unit 38 with usage 1.18455 . Total units tried = 5\n",
      "try to drop unit 38 from 5 th HD.  usage down to 1.153697613650843\n",
      "try to drop unit 38 from 10 th HD.  usage down to 1.124575149616936\n",
      "try to drop unit 38 from 15 th HD.  usage down to 1.107937337407423\n",
      "try to drop unit 38 from 20 th HD.  usage down to 1.0902675277688658\n",
      "try to drop unit 38 from 25 th HD.  usage down to 1.0678488519121703\n",
      "try to drop unit 38 from 30 th HD.  usage down to 1.0678488519121703\n",
      "try to drop unit 38 from 35 th HD.  usage down to 1.0678488519121703\n",
      "try to drop unit 38 from 40 th HD.  usage down to 1.0267451494339022\n",
      "all done trying to reduce usage of unit 38 final usage = 1.0172 4 sec elapsed 15 9 successful, failed patches, couldn't start= 16\n",
      "current avg and SD of usage are 1.00125 0.0417\n",
      "starting to reduce usage for unit 174 with usage 1.17201 . Total units tried = 6\n",
      "try to drop unit 174 from 6 th HD.  usage down to 1.1053615389462843\n",
      "try to drop unit 174 from 12 th HD.  usage down to 1.0465292952684455\n",
      "all done trying to reduce usage of unit 174 final usage = 1.0171 5 sec elapsed 14 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00115 0.04007\n",
      "starting to reduce usage for unit 291 with usage 1.16689 . Total units tried = 7\n",
      "try to drop unit 291 from 7 th HD.  usage down to 1.065533150364103\n",
      "all done trying to reduce usage of unit 291 final usage = 1.01899 5 sec elapsed 10 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00102 0.03911\n"
     ]
    }
   ],
   "source": [
    "#SECOND PATCHING BLOCK -- OVERUSERS.  applies a suppression of LONG STRINGS.  \n",
    "maxSD = 0.04 #0.06  #0.08  #0.04 \n",
    "print(maxSD,\"= default maxSD\")\n",
    "maxSD = float(input(\"enter maxSD\"))\n",
    "stopMaxUse = 1.02 #1.+  2.* maxSD  #0.5*maxSD  #don't be too aggressive; may create long chains\n",
    "print(\"default use threshold for moving on to next overused unit is\",r5(stopMaxUse) )\n",
    "stopMaxUse = float(input(\"enter updated stopMaxUse value\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage above\",stopMaxUse)\n",
    "nBigUsers = 5\n",
    "maxExchangePop = 0.25*aDP\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "print(\"this block reduces overuse, with exchanges up to\",int(maxExchangePop)) #\n",
    "maxGap = aDP - minDistrictPop\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        maxNtries +=1\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "nonfrozenList = list()\n",
    "for t in popHDlist:\n",
    "    if hasSplitUnit[t] != 1:  #don't mess with the small number of HDs that have to have a split muni\n",
    "        nonfrozenList.append(t)\n",
    "        \n",
    "attemptedBigUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to reduce up to\",maxNtries,\"units' overusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedBigUs) < maxNtries: \n",
    "    #simplified vs. vanillaHD - just take the biggest overuser\n",
    "    eligUnitUse = unitUse.copy()\n",
    "    for u in range(nUnits):\n",
    "        if u in attemptedBigUs: #we already tried this one, so lock it out\n",
    "            eligUnitUse[u] = -999.  #preventing re-selection\n",
    "    OUU = eligUnitUse.index(np.max(eligUnitUse))\n",
    "    attemptedBigUs.append(OUU)  #so we don't try this unit again in a future loop\n",
    "    if unitPop[OUU] > 0.25 * aDP:  #some overusers are high-pop.  If so, will drop only this unit, not any neighbors\n",
    "        OUUc = [OUU]\n",
    "    else:\n",
    "        OUUc = [OUU] + unitNbrs[OUU]\n",
    "    print(\"starting to reduce usage for unit\",OUU,\"with usage\",r5(unitUse[OUU]),\". Total units tried =\",len(attemptedBigUs) )\n",
    "    for u in OUUc.copy():\n",
    "        if unitUse[u] < 1.:\n",
    "            OUUc.remove(u)  #...drop any underused neighbors of the primary OUU from the target sheddable cluster\n",
    "    OUUcSet = set( OUUc)  #for muni-snap, overused are isolated.  So don't bother adding two-level neighbors to cluster\n",
    "    ouuHDs, ouuDists = list(), list()\n",
    "    for t in nonfrozenList: #popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if OUU in HDunitList[t] and homeU[t] != OUU: #can't drop the home muni\n",
    "            HDadjoinSet =   set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            OUUcAdjoinSet = set( getAdjoiners(list(OUUcSet),unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(OUUcAdjoinSet) ) > 0: #the OUU or one of its overused 1-neighbors adjoins the complement\n",
    "                ouuHDs.append(t)  #so we can shed the OOUc to the complement\n",
    "                ouuDists.append( unitCP[OUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo, idx0 = 0, 0, 0, 0, np.argsort(ouuDists)\n",
    "    while unitUse[OUU] > stopMaxUse and idxNo > -0.8*len(ouuHDs): #arbitrarily only examine 80% of HDs, biasing farthest ones\n",
    "        idxNo -=1\n",
    "        if idxNo % int(0.1*len(ouuHDs)) == 0:\n",
    "            print(\"try to drop unit\",OUU,\"from\",abs(idxNo),\"th HD.  usage down to\",unitUse[OUU] )\n",
    "        t = ouuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).difference(set(OUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        if not (contig and complementContig):  #dropping the cluster creates a problem (likely an HD discontig).  Try something simpler ...\n",
    "            if len(set(unitNbrs[OUU]).intersection(HDadjoinSet) )  > 0:  #Yay! The OUU itself on border.  Try dropping just it, not the full cluster\n",
    "                HDouuSet = {OUU}\n",
    "                trySet = set(HDunitList[t]).difference( {OUU} )\n",
    "                contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        else:\n",
    "            HDouuSet = set(HDunitList[t]).intersection(set(OUUc))\n",
    "        if contig and complementContig:  #we can at least drop the cluster, let's go for more\n",
    "            #HDouuSet = set(HDunitList[t]).intersection(set(OUUc))  #the subset of the OUU cluster that's in this HD.  Defined above\n",
    "            HDouuCpop = np.sum([unitPop[u] for u in HDouuSet])\n",
    "            giveUpOnShedding = False            \n",
    "            shedCandidates, shedScores = list(), list()\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if HDouuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward far, overused\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            while HDouuCpop < maxExchangePop and not giveUpOnShedding:\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                    if contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDouuCpop += unitPop[shedU]\n",
    "                        #print(\"shedding unit\",shedU,\"from HD\",t,\"total shed Pop now\", HDouuCpop)\n",
    "                        HDouuSet.add(shedU)\n",
    "                        trySet.remove(shedU)\n",
    "                        del shedScores[shedCandidates.index(shedU)]\n",
    "                        del shedCandidates[shedCandidates.index(shedU)]\n",
    "                        newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                        for u in newSheddables:\n",
    "                            if HDouuCpop + unitPop[u] <= maxExchangePop and u not in shedCandidates:\n",
    "                                shedCandidates.append(u)\n",
    "                                shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            shedSet = HDouuSet.copy()  #set(OUUc).intersection(set(HDunitList[t]))\n",
    "            trySet = set(HDunitList[t]).difference(shedSet) \n",
    "            gap = aDP - np.sum([unitPop[u] for u in trySet])\n",
    "            nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "            for u in trySet:\n",
    "                for uu in unitNbrs[u]:\n",
    "                    if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:\n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append(5.*(unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                        #bias toward UNDERUSED, close\n",
    "            addedSet = set( )    \n",
    "            stillGoing = True \n",
    "            while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "                nearHDscore2 = nearHDscore.copy()\n",
    "                for ij, uu in enumerate(nearHDlist):\n",
    "                    nHDnbrs = len( set(unitNbrs[uu]).intersection(trySet) )\n",
    "                    if nHDnbrs == 1 :  #BIAS AGAINST CREATING A SLIM CHAIN\n",
    "                        nearHDscore2[ij] *= 0.5   #make this score closer to zero (less negative) \n",
    "                idx, ij, notYetPicked = np.argsort(nearHDscore2), 0, True   #originally, used nearHDscore itself here\n",
    "                while ij < len(nearHDscore) and notYetPicked:        \n",
    "                    listNo = idx[ij]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                    unitNoToAdd = nearHDlist[listNo]  #add this unit ...                            \n",
    "                    canAdd  = wontEnclave(unitNoToAdd, list(trySet), unitNbrs, borderUnits)\n",
    "                    if canAdd:\n",
    "                        notYetPicked = False\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    stillGoing = False  #can't add any more units; we can't without creating an enclave\n",
    "                else:\n",
    "                    gap -= unitPop[unitNoToAdd]\n",
    "                    addedSet.add(unitNoToAdd)\n",
    "                    trySet.add( unitNoToAdd)\n",
    "                    for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                        if uu not in trySet and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:  \n",
    "                            nearHDlist.append(uu)\n",
    "                            nearHDscore.append(5.* (unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] ) \n",
    "                            #bias toward UNDERUSED, ~close\n",
    "                    del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                    del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                    for ijj, uu in enumerate(nearHDlist.copy()):\n",
    "                        if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                            del nearHDscore[nearHDlist.index(uu)]\n",
    "                            del nearHDlist[ nearHDlist.index(uu)]\n",
    "            currPop = np.sum([unitPop[u] for u in trySet])\n",
    "            if abs(currPop - aDP) <= maxGap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addedSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t]    = currPop\n",
    "                nPatchSuccess +=1\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "        else:\n",
    "            nCouldntStart +=1\n",
    "            #print(\"Due to discontiguity, can't drop OUU cluster for HD, OUU\", t, OUU)\n",
    "    print(\"all done trying to reduce usage of unit\",OUU,\"final usage =\",r5(unitUse[OUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "35140f52-2cb9-40e6-be15-ac02ba88316c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " patched use avg 1.00267 and SD 0.0394\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 8941\n",
      "working on HD 6400 out of 8941\n",
      "working on HD 4000 out of 8941\n",
      "working on HD 8800 out of 8941\n",
      "working on HD 4800 out of 8941\n",
      "working on HD 1600 out of 8941\n",
      "working on HD 5600 out of 8941\n",
      "working on HD 2400 out of 8941\n",
      "working on HD 800 out of 8941\n",
      "working on HD 8000 out of 8941\n",
      "working on HD 3200 out of 8941\n",
      "working on HD 7200 out of 8941\n",
      "all done checking HD and complement contiguity for all 8941 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse, HDvPop = [0.]*nUnits, [0.]*nUnits, [0.]*nHDs\n",
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(\"WARNING - we lost home unit\",homeU[t],\"from HD\",t)\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts       \n",
    "        HDvPop[t] += unitPop[u]\n",
    "    if hasSplitUnit[t] == 1:\n",
    "        unitUse[splitUnitNo[t]] -= (1. - splitUnitFrac[t]) * nDistricts * HDweight[t]\n",
    "        HDvPop[t]               -= (1. - splitUnitFrac[t]) * unitPop[splitUnitNo[t]]\n",
    "#    for u in unpatchedHDlist[t]:\n",
    "#        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "#plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "#unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\" patched use avg\", r5(patchedAvg),\"and SD\",r5(patchedSD) )\n",
    "#print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.axvline(0.95*aDP, ls=\"dotted\")\n",
    "plt.axvline(1.05*aDP, ls=\"dotted\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%800 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "da0951ea-df91-4017-b28a-22f20b64169b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of under,overpopped HDs after we correct below for splits 0 0\n",
      "there were 105 HDs with a split unit\n"
     ]
    }
   ],
   "source": [
    "nOver, nUnder = 0,0\n",
    "for t in popHDlist:\n",
    "    if HDvPop[t] < 0.95 * aDP:\n",
    "        nUnder +=1\n",
    "        plotPoly(HDCP[t].buffer(0.1))\n",
    "    if HDvPop[t] > 1.05 * aDP:\n",
    "        nOver +=1\n",
    "        plotPoly(HDCP[t].buffer(0.2))\n",
    "plt.show()\n",
    "print(\"number of under,overpopped HDs after we correct below for splits\",nUnder,nOver)\n",
    "print(\"there were\",np.sum(hasSplitUnit),\"HDs with a split unit\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "f22d96dd-ddfb-420a-bca9-9b624416045a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDsplitsPerUnit, HDweightSplit = [0]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    if hasSplitUnit[t] == 1:\n",
    "        HDsplitsPerUnit[splitUnitNo[t]] +=1\n",
    "        HDweightSplit[  splitUnitNo[t]] += nDistricts*HDweight[t]*splitUnitFrac[t]\n",
    "for u in range(nUnits):\n",
    "    if HDsplitsPerUnit[u] > 0:\n",
    "        plt.scatter(unitUse[u],HDsplitsPerUnit[u])\n",
    "plt.show()\n",
    "for u in range(nUnits):\n",
    "    if HDsplitsPerUnit[u] > 0:\n",
    "        plt.scatter(u,HDweightSplit[u])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "d3fceb02-48d5-4e4f-86b3-affadbb4fb4c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "displaying where these highly used split units are, and their associated HDs\n",
      "u, total use 180 0.9510872913191935\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "u, total use 377 0.9134317318812867\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "u, total use 432 0.9289381658071448\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "u, total use 1687 1.0089864040875487\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "u, total use 3355 0.8978364807430567\n"
     ]
    },
    {
     "data": {
      "image/png": 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GgXQNcIHISquLbtGiSKUg/JlIcgThmF/2lXHLvI3oNQr+OSVLbN3QCtYerCAj2kiYvuP1Ophtbl76eT8frjlETLCWudf248JeMe3i96TC6iJM3/F7xwTB30SSIwjApsNVPPDFdvolh/D21AFnVbG6thSm15BXYWX70WqyE0ICHU6TeLw+/rv+CP/5cR8uj497xnXjpuGp7WYzTJ9PosomhqsE4XREkiN0SC6Pj1eW7WdgShjndItscTuF1XbeW5XHe6vz6J0Ywn+u7CMSnFb097HprD1YwW0fbeLrO4cTZWzfVXo3H6niwS+3s7+0liv6J3DfuAyi2lllYbPdjdcnEd4Be8cEobWJJEfocHw+iXsXbOPbbYUAnJcRycMX9SA92tik810eH7/uL+PzDfn8tLuEILWSe8dlcNs5XQI2cfRsoVUpePP6/kx8dRXXvbOO//51SLuchOzx+nhl2QFeXX6AXvHBfHPHCLISggMd1mlVWF0AHXIIUBBam0hyhA5FkiSeXLyLxdsLef3afshl8Oz3e7jwpV+5emAiI9Ii0GuU6DUKgtRK9GolQRoFWpWCDYcq+W57ET/sLMbi8NA9xsiTk3oxuW+8qDHShqJNWj65ZQhXv7WWa99Zx6d/HdKu3qAPlVv5++dbySkwc9foNO4cldauk98qm0hyBKE+4pVd6FDmrszlg98O8dTkXlyUFQvAqO5RfLTmMK8sO8An6440eH5qhJ5pw1K4ODuWjGhju5g0ejZKizLw2a2Df090bhlMaIDfpCVJ4vMN+Ty5eBeRRg0Lpg+lX1L7XwVmtrkBCNaJYVZB+DOR5AgdxvyN+fzrf3u5e0w61w9JPvG4RqnglpFduGFYClanl1qXB5vTg9Xlxeb0UOv0YHN5SY82kBlrEolNO5EWZeTTvw7hmrfWct276/jklsGEBAUm0amodfLgVzn8uKuEqwcm8uglmR1mKw+Loy7JMYkkRxBO0TH+ioWz3k+7Spj9VQ7XDEpi5tj00x6jVMgJDpITHCRe7DuKbtFGPvnrYP7y9jque3cdH93U9j06y/eWcv+C7Xh9Pt68vj8X9Ixp0+ufKbPdjUYpbzervQShPWm/A82CcMymw5Xc8elmzu8RzdOTe4memE6me4yJj28eTGG1gymvrya3rLZNrutwe/nH1zu48f0NZMaZWPr3czpcggN1SY7oxRGE0xNJjtCu7Sup4aYPNtI7MYQXr+6DQi4SnM4oM87Eor8NR6mQM+W11azaX96q1yurcXLN22v574Z8Hp+QybwbB7a7peFNZba7xXwcQaiHSHKEdquw2s6099YTG6zl7akDRHd8J5cUHsRXfxtG78QQpr2/no/WHkaSJL9fZ3eRhUmvruJolZ35tw3lhuGpHbp30Gx3EyqGaAXhtESSI7RLVVYXU99bj0IuY95Ng8Qn1bOESavi/RsGct3gJB5dtINL5/7G2mP7XfnDT7tKuGzub4QEqfnmzuH0SQzxW9uBYraJnhxBqI9IcoR2x+7ycvO8DVRaXXx40yCiO+gwgtAySoWcJyb14uObB+P1SVz91lqmvbeeHQXmFrcpSRJv/ZLLXz/ayMj0CL64fSixwTo/Rh041XY3wTpRI0cQTkesrhLaFa9PYsZnW9hdVMN/bx1ClwDv7iwEzoj0CIanDed/O4p57oe9XPLKKi7JjmXasBT6J4Uib+L8LJfHx8MLc1iw6Sh3jOrKvednNPncjqDa5iK4g+wDJghtTSQ5QrshSRJPfruTn3aX8PbUAZ1iKEE4MzKZjPFZsZyfGc2Xm4/y8s8HWLx9DZFGDeMyoxnXM4buMUYiDZrTJi6VVhfTP97E1iPV/OfK3lzaLyEAd9G6xJwcQaifSHKEduPtXw8yb81hnpnSizE9ogMdjtCOKBVyrhqYxBX9E9mSX8X3OcV8v6P4RIVrjVJOYlgQCaE6nG4fFVYnFbUuKm0uwoLU/PfWwfRPDgvwXfifJElU29yEiC0dBOG0mjUnZ+7cuWRnZ2MymTCZTAwdOpTvv//+xPO5ublMmTKFyMhITCYTV155JSUlJU1uf86cOchkMv7+97+feKyyspK77rqLjIwMdDodSUlJ3H333ZjNLR+fF9qfb7YV8s8le7hzVBrXDk5u/AThrCSXy+ifHMYjl2SyatYofrrnXN6dNoBZF3ZnRFoESrmcCKOGYV0juHF4Cv+cksV3d4/slAkOQK3Tg8cnESImHgvCaTWrJychIYE5c+aQnp6OJEnMmzePSZMmsWXLFlJSUhg3bhy9e/dm2bJlADz66KNMmDCBtWvXIpc3nE9t2LCBN998k+zs7JMeLywspLCwkOeff57MzEwOHz7M9OnTKSws5Isvvmjm7Qrt0ZrcCu6bv41L+8Vz77hugQ5H6CBkMhlpUQbSos7eeVvVx/atCg3QdhiC0N7JpDMsRBEWFsZzzz1HYmIi48ePp6qqCpPJBIDZbCY0NJQffviBsWPH1ttGbW0t/fr14/XXX+fpp5+mT58+vPjii/Uev2DBAq677jqsVitKZdPyNIvFQnBwMGaz+UR8QuDtK6nhsrm/0TshhPduGIhaKRb8CUJT5Rw1M+HVVSy+awS94oMDHY4gtIozef9u8TuK1+vls88+w2q1MnToUJxOJzKZDI1Gc+IYrVaLXC5n1apVDbZ1xx13cPHFFzeYCP3R8RttKMFxOp1YLJaTvoT2pdjs4Ib31hMfomPudf1EgiMIzVRlcwFiB3JBqE+z31VycnIwGAxoNBqmT5/OwoULyczMZMiQIej1embNmoXNZsNqtXLffffh9XopKiqqt73PPvuMzZs38+yzzzbp+uXl5Tz11FPceuutDR737LPPEhwcfOIrMTGxWfcptK4ah5sb3l8PwAc3DsKoFS/SgtBc1fZjw1Vi4rEgnFazk5yMjAy2bt3KunXruP3225k2bRq7du0iMjKSBQsW8O2332IwGAgODqa6upp+/frVOx8nPz+fGTNm8Mknn6DVNl7wzWKxcPHFF5OZmcnjjz/e4LGzZ8/GbDaf+MrPz2/urQqtxOXxcfvHmymotvPBTYOICRbF/gShJaptLpRyGXq12PJEEE6n2UvI1Wo1aWlpAPTv358NGzbw0ksv8eabbzJu3Dhyc3MpLy9HqVQSEhJCTEwMXbp0OW1bmzZtorS0lH79+p14zOv18ssvv/Dqq6/idDpRKOr+eGtqarjwwgsxGo0sXLgQlarhT/4ajeakoTOhfZAkiQe/3M76vErm3TSIbtHGQIckCB1Wtc1NSJC6Q++9JQit6Yzr5Ph8PpxO50mPRUREALBs2TJKS0uZOHHiac8dM2YMOTk5Jz1244030r17d2bNmnUiwbFYLFxwwQVoNBq++eabJvX6CO3Tv3/Yx1dbCnj5mr4M7Roe6HAEoUOrS3LEUK8g1KdZSc7s2bMZP348SUlJ1NTU8Omnn7JixQqWLl0KwPvvv0+PHj2IjIxkzZo1zJgxg5kzZ5KRkXGijTFjxjBlyhTuvPNOjEYjvXr1Oukaer2e8PDwE49bLBbGjRuHzWbj448/PmkScWRk5IlESGj/Pll3mFeXH2D2+O5M7B0X6HAEocOrtrlEtWNBaECzkpzS0lKmTp1KUVERwcHBZGdns3TpUs4//3wA9u7dy+zZs6msrCQlJYWHH36YmTNnntTG8eGsptq8eTPr1q0DODFMdlxeXh4pKSnNuQUhQH7eXcKji3YwbWgyt55z+uFLQRCaR2zOKQgNO+M6OR2FqJMTONvyq7n6rbWMTI9g7nX9UXSizREFIZCmvL6atEgDz13RO9ChCEKrCUidHEFoisMVVm76YAM9Yo28fE1fkeAIgh+ZxZwcQWiQSHKEVlNpdXHD+xsw6VS8M20gWpWYPyUI/lRlcxEitnQQhHqJJEdoFXaXl5vnbaDG4WbejYMIE8XKBMGvfD4Js1305AhCQ854Cbkg/JnXJzHjsy3sKarhs1uHkBQeFOiQBKHTqXF48EkQIiYeC0K9RE+O4FeSJPHEtzv5aXcJr13bl96JIYEOSRA6pWp73b5VYgm5INRP9OQIfvXWLwf5cM1h/jkli9HdowMdjiB0WlW2un2rgkWSIwj1Ej05gt98vbWAZ7/fw12j0/jL4KRAhyMInVq17XhPjhiuEoT6iCRH8Itf95dx34JtXNYvgXvO7xbocASh0zMf24FcTDwWhPqJJEc4YzlHzUz/aBMj0iKYc1mW2CxQENpAldWFWilHJ0ozCEK9RJIjnJH9JTXc8P560qKNvHZtP1QK8SslCG2h2u4mRKcSHyoEoQHiHUlosbUHK7j8jTVEGjV8cMNAgtRiHrsgtJVqm1vMxxGERogkR2iRrzYf5fp319Er3sTntw0lVBT7E4Q2VW1ziZVVgtAI8dFbaBZJknjxp/289PN+rhyQwNOTs1ArRa4sCG3t+HCVIAj1E0mO0GROj5cHv8xh4ZYC7r8gg7+d11XMBxCEADHb3aRFGgIdhiC0ayLJEZqkxuHmto82sfFwFa9c05cJveMCHZIgnNXMdjfBoidHEBokxhmEJlm5r4zfcitICNURpFbg80mBDkkQzmoWuweTSHIEoUEiyRGa5KJesbxxXX9CdCpunreR8S/9SqXVFeiwBOGsJEkSFtGTIwiNEkmO0CRyuYwLe8Xw1d+GM7F3HEerbIjZOIIQGE6PD5fXh0knZhwIQkNEkiM0S36ljf/tKOa2c7uKZeOCECDHt3QQPTmC0DCR5AjN8tzSvYQEqbhlZGqgQxGEs5blWJJj0ookRxAaIpIcockOlNbw7fZC/j62m6huLAgBJHpyBKFpRJIjNNnry3OJMWm5vH9CoEMRhLPa8SRHrK4ShIaJJEdokiMVNr7eVsit53QRFY4FIcAsDtGTIwhNIcYchCZ585dcQnQqrh6YFOhQWsTrk9hdZGF3kQWFXMa4njEYNOLXX+iYzDY3aqUcrUoR6FAEoV0Tr/JCo0osDhZsPMqMseno1B3vRfXX/WU89vVO8sqtJx4L1u3i6cm9ROVmoUOyODxi0rEgNIFIcoRGvf3LQRRyGdcPTT7xWH6ljZd/3k9+lY33bhjYLiciF5sdPPXdLr7bXsTg1DCentyL/smhVFpdzPpyO88u2c3FWbHI5aLij9Cx1G3p0P7+5gShvRF/JUKjlu4qxu72cscnm5HJZBSb7ewrqT3xvErRvuboSJLEB78d4vmle9GpFbxwVW8m94k/sZloXIiOGWPSufyNNazLq2Ro1/AARywIzWOxu8WkY0FoApHkCI364MZBfJ9TxJYj1SgVMoZ2CefWc7ry0Fc5eHw+bvpgA5P7xDOuZzTGAHeh21weHlm0g682F3D9kGTuuyDjtJMz+yeHkhCqY/H2QpHkCB1OUzfnlFwu3IWFeGtq8NXWIrlcyA0G5AYjyohwFGFhJ5J/QeiMRJIjNKprpIE7R6ef8viY7lEs2VHE11sLuXfBNjQL5YzNjGZS7zjOy4hq81VYPp/E+f/5hYJqOy9d3YdJfeLrPVYmkzG6exT/21HMo5dkigmcQoditruJNmlPedxdWor1l1+wrlmLc99enHmHwOOptx1FaCiabt3QZWdhOOccdH37IlP6721BkiQOVB9gR/kO9lfv50DVASodldS6a6l116KWqzGoDRhVRpJMSaSFpNEttBv9o/sTpAryWxzC2UsmSdJZsZ20xWIhODgYs9mMyWQKdDidTkG1nW+3FfL11kJ2F1kI1qm4KCuGSX3iGZQS1urzXrbmV/PU4l1sOlzFbed2Yfb4Ho2ec6jcytj/rOS+CzKYfm7XVo1PEPxp/Eu/MiA5lKcm98JntWJe/B3VCxbg2LED5HK0Wb3Q9eyJJj0ddUoKiuBg5EYjMpUKn9WKr6YGd3EJzgMHcO7bh23TJrwVFciNRowXjCP0mmvQ9ezZotgkSWJjyUa+z/ueXwt+pdhajAwZicZE0kLSiAqKwqA2oFfpcXvd1LprMTvNHLIc4kD1AaxuKyq5igHRAzg38Vwu6XIJwZpgP/8EhY7kTN6/RZIj+N2+khq+3lrA11sLOVplJ8KgIS1KT1JYEImhQSSGBZEYpiMxNIhIo+aMussLqu089789LNpaSPcYI/+Y0LNZw0+Pfb2Dzzbk8/iEnlwzKFF03QsdwvA5y7iym4mrc5dT/fl8fDYbhnPPxXTRePQjRqAMDW1We5LPh2PnTmqXL6f6q4V4iovR9e5NxJ13Yhg5oklt2D12Fh1YxOd7PifXnEuCIYFzE8/lnPhz6BPVp0k9M5IkcdhymNWFq/nl6C+sL16PUqZkfOp4ru1xLRlhGc26L6FzEElOE4gkp+1JksTmI1X8vLuUw5U2jlbayK+yU2l1nThGo5STEKqrS4DCgog0aFAq5KgUMlQKOUqFDJVcjkopQymve1wpl6NSyvntQDkf/HYIo1bF/Rd04/L+iSia2WPkcHt5cvEuPl13hAm94/jnlF4Bn1ckCA3xuVw8fP1jXLP/JzRIhF77F0KvvhpVfP3Ds80heTzULF9O5fsfYN+8Gf2wYUQ9cD/a7t1Pe7zX5+Xbg9/y6pZXKbeXMzppNFdlXMWgmEFn/KGh3F7OV/u/Yv7e+ZTaSpnQdQJ39b2LGH3MGbUrdCwiyWkCkeS0H7VOD0erbORX2jlSaSO/0nbi+wqrC4/Ph9vjw+2TcHt91PcbqlcruHlEKree2/WMC/t9u62Q2V/lEKxT8eSknozpEX1G7QlCa3Ds3UfBAw9g37ef6lHjGfLkgygjIlrlWpIkUbtsGaXPPY8rP5+I6dOJuH36SXN29lXt45FVj7C7cjfjkscxo98Mkkz+Lxjq8Xn4av9XvLb1NaxuK9N7T+fGnjeikIu5dGcDkeQ0gUhyOi7vsWTH45OOJT8+3F6JYJ3Kr1WLD1dYOe/5FUzIjuPla/r6rV1BOFOSJFH14YeUPv9vFElJ3JY4kfvvmMD4rNjWv7bbTfkbb1L+xhtoe/Yk/t/Po0yI56NdH/HS5pdINiXzj6H/oE9Un1aPxeq28sa2N5i3cx59o/ryzIhnSDCKvfQ6uzN5/xarq4R2TyGX/f6JTdN610kO19MrLhiDtv4/iyKznTdW5KJVKxjWNYJzu0W2XkCCQF2SUfTEE5i/+JKwaVOxT7uNgy+vabN9q2QqFZF31c3NKbj/AfKuuoovbk7jM+UWrs+8nhn9ZqBRtOIf5h/oVXruHXAv5yacy8OrHubKb6/khVEvMDh2cJtcX+h42lcVN0EIsFqnp97eoYpaJ9e9s45vthXyxcajPPDFtjaOTjjbeGut5N82HfPX3xD77LNEz56NxVf3st3WxQB1ffpgmvc6h0xOLnlhA2+rbuaBgQ+0WYLzRwNiBvDFxC/oFdGL6T9O5+sDX7d5DELHIJIcQfiDWqcH/Wm2qKhxuLnh/Q2Y7W6++ttwHhzfnRKLE4fbG4AohbOBz+Hg6O23Y9++naS33yZkymQALPa6ujdtvQN5qa2UG9bezb+vN6E6dzjBz7xDzc8/t2kMf2RUG3lt7GtMSpvEI6sf4ZPdnwQsFqH9EkmOIPyB1ek5Zbhq7cEKLn55FYcqrMy7aRCpEXoSQuuWwxZW2wMRptDJSS4XR2fMwL5jB4lvvYl+yO/DMWa7G2jbnpwqRxW3/nArLq+L9yZ+RI+X3sA4diwFf5+J9bff2iyOP1PJVfxj6D+YljmNOevnsHD/woDFIrRPIskRhGO8Pgmby4tBUzf/p7zWyT3zt3L1W2uJMmr45s4R9IyrK0qWEKoD4GiVSHIE/yt+6ilsv60h4dVXCOrX76TnLA43MhkY/TjpviEOj4Pbf7qdKmcVb497mwRjAjKlkvjn/kXQ0CHk33kXztzcNonldGQyGfcOuJfLu13O42seZ/mR5QGLRWh/RJIjCMeU1zoB0GuUfLLuMGP+vZJle0qZc2kW828bSmqE/sSxscFaFHKZSHIEv6v+8kuqF3xBzOP/wDB8+CnPm+1ujBplq1cRh7pVXU+vfZrc6lzeGPsGqcGpJ56TqdUkvPgi6vg4jt51N95aa6vHUx+ZTMYjgx9hdOJoHlr1EIcthwMWi9C+iCRHEI7ZU1wDwOPf7OThhTsYlxnNz/ecy9WDkk55Q1Eq5MSYtBytsgUiVKGTcuzZQ/ETTxJyxeWEXHbZaY9pyx3Iv9z/JV/nfs1jQx+jR/ipW6XIg4KIf+llPCUlFD/2KIGsSKKQK3hq+FNE6CKYuWImNrf42xREkiMIJ5yTHsEdo7oSH6JjwfShPHdFb8IN9a8cSQjViZ4cwW8kj4fChx5CnZpK9COP1HtcU3cgP1OHLYeZs34OV3a7kgldJ9R7nKZLKrFPPYllyffU/PBjq8fVEIPawAvnvcDRmqO8uPnFgMYitA8iyRGEY2QyGfdf0J2v7xzBwJSwRo9PCA0iX/TkCH5SOW8ezj17iX36KeSa+pNri8ODqZW3HpEkiSfXPEmELoL7Bt7X6PHG8eMxjBlD8dNP4bVYWjW2xqSFpnFnnzv5bM9nbCsTZR7OdiLJEYQWEj05gr+4i4ooe+VVwq6/Dl1WVoPHtkVPzte5X7O+eD2PDXkMnVLX6PEymYyYRx9Bstkpe/GlVo2tKa7tcS2Z4Zk8/tvjuH3uQIcjBJBIcgShBfLKrRytslNWI2rlCGeufO4byHU6Iu66u9FjWzvJcXgcvLz5ZcanjGdY/LAmn6eKiSHi9ulULViA6+jRVouvKRRyBf8Y+g9yq3NZdGBRQGMRAkskOYLQAle/tYavtxYwODWs2TufC8IfuY4cofqrrwi/5RYUBn2jx9fY3Zh0rbd8/PO9n1PpqOSuvnc1+9zQv/wFRXAw5a/PbYXImqdHeA8uTLmQN7e9idPrDHQ4QoCIJEcQWqBXXDD9k0P5/LahqBTiz0houfK33kIRGkLoX65p0vGt2ZNjc9t4N+ddJqdNJtGU2Ozz5UFBRNz6V8yLFgW8Nwfg9j63U2Yv44t9XwQ6FCFAxKuzILTAqO5RbDxcRY1DjPcLLee1WLAs/o6wa69Frmt87oskSVgcrbeEfEneEswuM3/N/muL2wi54grkej3Vn8/3Y2QtkxqcyoUpF/Lp7k/xSb5AhyMEgEhyBKGJisx2vttexJPf7uJf/9uD1ydxqFysrhJazvz1N0geT701cf7M7vbi9kqt0pMjSRLz985nZPxI4g3xLW5HrtMRPHky1V9+ieRy+THClrkq4yqO1BxhXdG6QIciBEDb1AUXhA7G7fWxu8jCpsNVbDpcxebDVRSaHQAkhukY3T2KQanhdI81BjhSoSOrnj8f49ixKCMjm3T88c05W2MJ+c6Kneyu3M2dfe8847ZCr7qSqo8+ombZMkwXXuiH6Fqub1Rf0kLSmL93PkPjhgY0FqHtiSRHEI7JOWpmyY4iNh+uYtvRahxuH2qlnKz4YC7pHUe/pFD6JYcQZdQGOlShE3Dm5eHcv5/Iv89o8jmtuTnndwe/I1IXyfC4U7eSaC5NWhqazB7U/PBjwJMcmUzGlLQpvLj5RaxuK3pV45O7hc5DJDnC2cvjhKrDEJ4Gcjn3LthKaY2ToV3CuW9cBv2SQ+kZZ0KjVAQ6UqETql22DJlGg35Y05dpH09ygv28ukqSJJbnL+e8xPNQyP3z+24cPYbKDz5AcrmQqdV+abOlRieN5rmNz7G6YDXjUsYFNBahbYkkRzh72Kshfz0cWQNH1kLBJvA64cbvIXkYxWYHfxuVxvRzuwY6UuEsULNsOfphw5o04fg4Syv15ByoPkBBbQGjEkf5rU3j6FGUv/oq1g0bTrvRaFtKMCaQHprO8vzlIsk5y4gkR+ic3A6wFEDhlt+TmpKdgAT6KEgaAgNuhHVvgFyFw+3F4vAQ2cBeVYLgLz6nE/v27UTPmtWs804MV/l5Ts5vhb+hVWgZFDvIb21qevRAERaGbePGgCc5AOcmnMtX+79CkiRkMlHb6mwhkhyhc/rgorqeGoDw9LqkZsjf6v4N6wIyGeQur0ty9BGU1dQVCyustrPpcBXBOiUmrQqTToVGKRcvioJfOXbtArcbXe/ezTrP4nCjUcrRqvw7hLqjJIdRmuF4c8yYy+xIdg8+hwfJ7UOmViDXKpAHqVBFB6GMDkIZrkPWSBFMmUyGLjsbx7btfo21pfpE9uGdnHcoqC0gwZgQ6HCENiKSHKFziu5Vl+TcdwAM9axcsVXU/auPRG6XoVbK+feP+/j3j/tOOkylkJEWZeS7u0YgF9WNBT9w5OQgU6vRZnRr1nlnUghw3LhxFBcXI5fLMRqN/OeZ5+ihTMKxt5Lb912EWlJRuWkvcoMKuV6FXKtEppIjmZ34HB58tW58trrVXTKNAm23ULQZoWi7h6EwnH7Oja53NhXvf4Dk8yGTB7ZiSVZk3Z5gOeU5Isk5i4gkR+icVDqI7FF/ggNgLQOlDtR64jUytj02jmq7C4vdQ43DjcXhxmL38OOuEn7cVYLozBH8xbF7D5qMjGZPyLXYPS2ejzN//nyCTcE49lcx/9WPmHb5dfxwywfIk4OYF/kNY4ZexIjeo5AHnb59SZLw1bpxF1txHbbg2FtF1Zf7QS4jKCsC/dA41EnGk3o9tT174rNYcBcWoU74vfbOnxOul19+mb59+7bovpoqTBtGvCGeneU7GZ86vkVteD0+KousVBZaqSysxVrtwmn34HZ4kMllaHRK1DolpggdYXF6wuMNmCK0oic4gESSI3RONcVgiGr4GGsZ6CM5nr3o1Ap0ah2xwScfdrCsls0GtXihEvzGffQo6sTmb5vQ0p4cSZLQlvgo/WAz7mIb1RVVKEO0xD02hO2WHXz1/c/8JeP2ehMcqBt+UhjVKIxqtOmhmMYm4611YdtcSu3aImxbt6FODSbk4lTUCXX1o1TH7tF99OhJSc78+fMJCQkBYOHChdxwww1s27at2ffVXCnBKRypOdKscxxWNwe3lnE4p4L83ZW4nXUb8hrDtBjCNKh1SoKCNfi8Em6Hh5oqJwe3luE81utlCNOQ0iuC5KxwkjLDkIttYNpUs5KcuXPnMnfuXA4dOgRAz549eeyxxxg/vi4rzs3N5b777mPVqlU4nU4uvPBCXnnlFaKjo5vU/pw5c5g9ezYzZszgxRdfPPG4w+Hg3nvv5bPPPsPpdHLBBRfw+uuvN7ld4SxUWwrBjXRJW8tAH9FoU2W1LiLEhGTBj1wFR9H16dPs8ywONyZt8z6busvtVH99AOf+au5Z8S9+O7IFmULGkiVLkGuVFBQWALSoyrHCoMZ4TgKGEfE49lRiXnqI0le3ousTScglXVDFxdXFUHAUGHzivOMJDoDZbG6zDxDx+ni2lm1t0rFlR2rYvuIo+zeU4PP4iE4Npt+FycR3CyU8To+6gWX8kiRhM7soy6/hyK5KDueUs+OXAgyhGnqOjCNzRDxBpsAuqz9bNOuvJSEhgTlz5pCeno4kScybN49JkyaxZcsWUlJSGDduHL1792bZsmUAPProo0yYMIG1a9cib2Q8dsOGDbz55ptkZ2ef8tzMmTP57rvvWLBgAcHBwdx5551ceumlrF69ujnhC2eT2hJI6N/wMdbyup6cRpTXOgmvZ86BIDSX5PXiKS5BFd/8pMJsdxMX3LRilJIkYV1fjHnxQeRGNeHXZ/L5s98gk8mYN28es2bNYsmSJRTWFhKsCcagNjQ7nuNkchm6zHC0GWHYNpVgXppHyYubCb0sHWVkJO6CwlPOmTp1KsuXLwdgyZIlLb52c8Qb4/ku77sGV1hVFVv57atcDm0vxxCmYeDFKfQYFtespEQmk6EP0aAP0ZCSFYF0ZTrl+bXsWHmUTd8fZuP3h+kzJpF+FyQ3mCwJZ65ZP90JEyac9P0zzzzD3LlzWbt2LQUFBRw6dIgtW7ZgMpkAmDdvHqGhoSxbtoyxY8fW225tbS3XXnstb7/9Nk8//fRJz5nNZt59910+/fRTRo8eDcD7779Pjx49WLt2LUOGDGnOLQhni9pSMDTS02ctg4iMRpuqqHXSJbLlbwCC8Ec+ux18PhSm5m8JYrG76RHT+Hk+l5eqz/di31mBflAMwRd3Qa75fUXWtGnTmD59OhUVFVQ6KgnXhjc7ltORKWToB8Wg7RFG1Zf7qZi3C1XGZLy1tacc++GHHwKclHC1tnBtOFa3FbfPjVpxctLidnpZsyiXHSvrelzOvymTtAHRfllsIJPJiEwyMur6Hgy9NI2tPx5h68/57FpdyLBL08gYEiOGw1tJiwcHvV4vn332GVarlaFDh+J0OpHJZGg0v3fra7Va5HI5q1atarCtO+64g4svvvi0idCmTZtwu90nPde9e3eSkpJYs2ZNS8MXOjOXFVw1TUty9I2/uJeL4SrBj3y2uk1dZc0oAnicxd74DuTeGhdlb27Hsb+K8Ot7EHppOhZ7DYWFv/emLFq0iPDwcMLCwrB77OiUzY+lIQqjmvBpmYRM7IoivD+emgx8Lu9pj502bRrLly+noqLCrzGczvH7tHvsJz1ekmfh82fWs3t1IUMnd+Xax4fQbVBMq6ym1OpVDJncleueHEJijzB+nreb/721A3tt4Dcz7Yya3U+Wk5PD0KFDcTgcGAwGFi5cSGZmJpGRkej1embNmsU///lPJEniwQcfxOv1UlRUVG97n332GZs3b2bDhg2nfb64uBi1Wn3SGC5AdHQ0xcXF9bbrdDpxOp0nvrdYLM27UaHjqi2t+7fRicdNH66KEMNVgp9I9ro3WLkuqNnnNjbx2FPpoOyt7Ug+icjbeqOOr+uBNJvNXHHFFdjtduRyOZGRkSxevBiZTNYqSQ7U9V4YhsVR+OAMdANvpeyt7UTenIXFWYvNZiPu2HydPyZcrc3jq5sMXOmoJFhTt8Jg+/J8Vi04QGSigUvu6E1IdPP/v7SEIVTL+Tf1pEufSJZ/sofPn1rPRX/LJirZ1CbXP1s0O8nJyMhg69atmM1mvvjiC6ZNm8bKlSvJzMxkwYIF3H777bz88svI5XKuueYa+vXrV+98nPz8fGbMmMGPP/6IVuvfTQ+fffZZnnjiCb+2KXQQJ5KcBnpyXDZw1Taa5NhcHmwur+jJEfxHkur+bebwhMfrw+ry1lvt2GtxUvZODjKFjMjpvVGG/P47m5yczPr160973umGbvzJW7oD26p/oQh+kvL3d2Ada+Kq664+bcLV2o6vrMqvySfZmMLqL/azfdlReo9NZOiUrigCsPKpa78oYroE8/2bOSz892bG3dKL1OzGF0QITdPsJEetVpOWlgZA//792bBhAy+99BJvvvkm48aNIzc3l/LycpRKJSEhIcTExNClS5fTtrVp0yZKS0vp16/fice8Xi+//PILr776Kk6nk5iYGFwuF9XV1Sf15pSUlBATE1NvnLNnz+aee+458b3FYiGxBUs2hQ6otqTu34aSHFt53b+NrK6qONaFLJIcwV9kx3pwJIe9kSNPZnHU9UKcbrjKa3VT9k4OeH1E/CnBaYxGoaHSUdmsWJpDm52NNqMb4Tf2ouztHAy/KFj321pkyrZPKNJC6t67uhi78uO7O8ndXMq513Sj17mBLQ6oD9EweWZffnp/F9/P3c6o63vQY1hsQGPqLM74t8zn8500LAQQERFBSEgIy5Yto7S0lIkTJ5723DFjxpCTk8PWrVtPfA0YMIBrr72WrVu3olAo6N+/PyqVip9//vnEeXv37uXIkSMMHTq03rg0Gg0mk+mkL+EsUVsCchVoQ+o/xlpW928jPTlltXW/22J1leAvcl1dr7XP3swk58TmnCd/NpV8EpWf78VX6ybiliyUoc3rFdcqtafMUfEnyW5DptWhTjQScUMmzjwz1d8dbLXrNcQreUGSseOrcnK3lHHhbVkBT3COU6oVXPDXXvQYEcfyj3ZzYFNpoEPqFJrVkzN79mzGjx9PUlISNTU1fPrpp6xYsYKlS5cCv696ioyMZM2aNcyYMYOZM2eSkfH7CpYxY8YwZcoU7rzzToxGI7169TrpGnq9nvDw8BOPBwcHc/PNN3PPPfcQFhaGyWTirrvuYujQoWJllXB6tSV183EaKltgPd6T03CSI3pyBH+TB9X15Hhrapp13vHNOf88J8fy8xGc+6uIuLEXqsjmzyfRKXXY3LZmn9dU3ppa5Pq6uDRdQgiZ0IXqRblokkwE9W1k3pyf2T12hh2aTG5JBefflEmXPo3PyWtLMrmM867JwO3w8uN7O1HrFCRl+mfl29mqWUlOaWkpU6dOpaioiODgYLKzs1m6dCnnn38+UNfDMnv2bCorK0lJSeHhhx9m5syZJ7VxfDirOV544QXkcjmXXXbZScUABeG0akvqdiDf8A7owiAoHILCjv13WN2WD8d7coIaHq4qr3Uik0GYXvTkCP4hUypRRkXhLjy1dkxDTpfkOHKrqVl2BNPYZLTdQlsUT4QugjJ7Wavszi253XhKS1HFxp14TD84FtfhGqq+2o86yYgy3P+TnutTvNlOdvF5nHN1N7oNrH+6QyDJ5DLG3NADl93DD+/s5MqHBmKKaLufUWfTrCTn3XffbfD5OXPmMGfOnAaPOV4tuT4rVqw45TGtVstrr73Ga6+91liIglC3Z5UmGJY8ANJplq2qgkCuBG0wKBtOXsprnIQFqVGIjTkFP1IlJOAuKGjWORbH8eGquiRHcnup/mo/6mQTxlEtn28Yb4jH6rZicVlOrDjyF3dxMfh8qP6wpYNMJiNkShrOQ2aqFh4g4uZebTLpuCy/Bs/KCEoS95B13uhWv96ZUCjknH9TJvP/uYHv38zhsvv7o1T7d+f5s4UotSh0PkP/VvclSeC0gK2y7sv+p3/DTj8h/o8qrKJGjuB/qoR43PlHm3WO2e5GLgODuu5l2/JzPp5qJ9HTeiI7gyQ8wVA3J+Vo7VH/Jzn5+QCo/1TdWa5WEDolnfL3dmDbXIq+f+tu0eNxeVn69g7sBjO2wYGZD9RcmiAVF96WxZf/2sRvC3M556rm7Vgv1BFJjtB5yWR1vTXaYAhLbVETZbVOIoxiqErwL223btT+9DOS14tM0bRP6Ba7B6NWhVwuw1PpoOaXo5hGJ6KKOrO6LkmmJAByq3PpGd7zjNr6M8fu3ciCgk5s1PlH2m6h6PpEYl6Sh65XxEkVmf1tw5JD1FQ6WNX/c8aEjWy16/hbZKKRIZO6sPrLA3QbGE1MF/8moWcDsR2qIDSgvMZJuF705Aj+pc3Kxmez4TyQ2+Rz/lgI0PLzEeRBSgznnPnKIKPaSIophZyynDNu68/s27ajy8ysN5ELviAFn8ND7ZrmzU9qjvKjtWz94Qjdx0RwUL6HXhG9Gj+pHckenUhUkpHlH+/B6/EFOpwORyQ5gtAAMVwltAZdr54gl2Pfvq3J51gcbkw6Je4yG7bNJRhHJSL30zyNrIgscspbIcnZvh1t71M3XT5OGapFPzCGmpVH8R2rA+Rvq7/YT3CUDld2XeX9rIisVrlOa5HLZZx3XXeqiqzs/LX1ksHOSiQ5gtCAcjFcJbQCuV6PtkcPbM3Yf89yrCendlUBcoMawyD/FYvrHdmbvZV7qXWdupFmSzkP5uEpLiaof/8GjzONSkRyebGur3+bnpYq2FfF0T1VDJnUla0VW4jVxxIZ1L6WjTdFZKKRboNi2PS/Q3jq2QNMOD2R5AhCPdxeH9U2NxFiuEpoBYbRo6j95VckV9M2ZrQ4PESolNi2lGEYHINM5b+X7+Hxw/FIHlYXrvZbm7XLlyHTatE3ULQVQBGsQdcrAuv6YqTjW174gSRJrPvmIJFJRlJ6h7M8fzkj4zvOfJw/G3hJCvYaNzkrm7cq72wnkhxBqMeJQoCiJ0doBcbRo/HV1mKtZ3PiP7PY3QywSkgeL3o/13hJMCaQHprOivwVfmuz5udl6IcNQ96E3dYNg2PxlNtx5pr9dv2SQxaKDpgZeHEKueZcCmoLOC/xPL+139aCI4PIGBLDtp/z8XnF3JymEkmOINSj/NiWDmJOjtAaNN27o0pIwPLdkiYdb3G46VXlQZsRhiLY/7+ToxJHsfLoSpxeZ+MHN8JdUIB9yxaMY8Y06Xh1qgllpA7bppIzvvZxO38pwBiuJTkrgp+O/ESQMojBsYP91n4gZJ+XgLXayaGcikCH0mGIJeSCUI/yE/tWiSRH8D+ZTEbI5ZdT/sYbRD84C0Uj++sprB4ibQp0Wa2zQ/UlXS7hre1v8dPhnxgVPpzSw3mUHzlEZeFRHLU1uOx23E4nKo0GTZAendFIWHwiEYkpRKakojMYT7RVtWABcr0e04UXNOnaMpmsbshqXRGSV0KmOLPigA6rm/0bSxl4cQoSPhbuX8gFKRe06m7rbSEyyUhUiomdvxa0uy0p2iuR5AhCPcqPDVeFiy0dhFYSctmllL36KuavvyHs+uvqPU6SJHrZJXwy0GaEtUosQRVeLi7IZMtzb7Gnci4ASrWG0Lh4gkzBaHRB6ENCcTsdOKy1VBYeZcfyH/F6PCCTEZvWjdS+A0jrN4jqL78keOJE5Hp9k6+vywynZnk+rsNmNF1CzuheDm4pw+fx0X1oLKsLV1NkLeLKjCvPqM32oueIOJZ/sgebxUWQSbw2NUYkOYJQj4paJ0atEq1KlFMXWocyMhLj2LFUfvQRoVdfhUylOu1xTo+PgZKC2kgtCv3pj2kJj8vFnt9+YevS7yg5uJ+YIA37QixcdsNf6df3PIKjopHL6//993m9VBUXUrRvDwe3bGDjt1/x2/xPCDOpGdAzg0iPB4WyaW8zqngDcqMa+57KM05y8raVEZsWgj5Yw6cbPqVHWA+/FzoMlNTeEaz4BA7llJM5PK7xE85yYk6OINSjvNYp5uMIrS5i+m24jxzB/PXX9R5jtrnIQoEr9syqGx8n+XzsXPkz7/39NpbOfRGd0cjkBx7l9rc+IW+Elm+16wmNiWswwQGQKxSExyfSa9T5TLznIW6fO48BtR4UoaH8MP9D5t33N/av+61Jq6ZkchmaVBOuw83bnf3P3E4v+XuqSMmOYFvZNlYXrGZaz2ltsj9WW9AZ1cR0DSZvW/M2uj5biZ4cQahHea2LCIPoDhZal7Z7d4wXXkjZ669jmjgRufrU37naUiuhyKmMN5zx9UoOHuCHN1+h9FAu6YOHcfkjTxEW93vl5Om9p/PI6kfYWbGz2b0fNd8uJurgEQYvWoRZrWDVf+fxzX/+SVxGJuNuu4vw+IY3ElUnGjHvOozk9SFTtOwzeMG+KrxuH6nZEdy/5SnSQtIYnzq+RW21VynZEWz4Ng+vx4dCKfoqGiJ+OoJQD9GTI7SVyLvuxFNSSuV77532efuRuiJ9msSGJyc3xOfzsm7hfD595F4Arn7yOSbe89BJCQ7AxV0uJsWUwrhx48jOzqZPnz6MHDmSLVu2NNi+12ym7OVXMF10EdqMbkSnduWyh57ksoefwl5j4eMH/86WpYsb7NVRJxrB48NdbGvxfRYfNKMzqtjp3sLaorXc0ecO5LLO9VYXlxaCx+2josB/xRs7q871f14Q/Ki81kW46MkR2oCma1fCb7yB8tfn4szLO+V5b5mNCnyYwrUtat9eW8MXTz/K6s8/ZuDEy/jLM88Tn9HjtMcq5UoeGPgAwTcH88zCZ9i6dSv33HMPN9xwQ4PXKHnuOSSnk6gHHjjp8ZTsvlw/50V6jRrLsvfe4Jt/P4Pb4ThtG6qYuonKnrKWJzkleRYikg08ve5pBsYMZExS05axdyQRiQbkChkleZZAh9LuiSRHEOohenKEthRxxx0oo6MpfvQxJO/JpfulaidF+DBpmz/puLqkmP8+ej9lRw5xxWPPMOLqqSiUDbczMmEkl/S6hH9t+BdVjirMZnODc1qsa9di/uJLou69F1V01CnPqzRaxtx0O5MfeJTD27fy+ROzsVZXnXKcXKtEplPiqTp9EtQYSZIoPVxDnnYXpbZSHhvyWKvPxWluj5c/KFUKIhIMlBwSSU5jRJIjCKfh80lUis05hTYk1+mIfeopbJs2Uf7aayc9p6hxU4JEUDM35Kw4eoT/Pnofks/LX556jsTMpm9OOWvgLPa+vpekpCQeffRRPvroo9Me5y4tpeD++wkaPJiQK69osM2u/Qdz1RP/h7Wqgk8fuRdLeekpxyjDtHirWlaQ0F7jxmX38HPNEqb3nk5KcEqL2mmO+fPns3379ib3ePlLWKye6pKW93idLUSSIwinUW134/VJYuKx0Kb0QwYTOeNuyl+fS82KFSceV9k9mJU0q1eiuriIBU8/QlBwCNc89TyhsfHNiiVcF86Xn35J6nOpjL1tLLNmzTrlGMntpmDmPciQEf/8c8jkjb+lRKd25Zqn/41MJmPBUw+f0qOjMKnxmluW5Bw6WrevU3J8LDf1uqlFbTRXSEjIif9urMfLn4zhWmoqWtbjdTYRq6uETsnu8rLhUCWrD5RzoLQWm8tLsE5FmEGNSavCqFWSEKojXK8hTK8mJEiFQatEr1aikMvElg5CwITfeiv2bdspvP8Bkud9gDYzE7lHwteMDTmt1VUsePoR1Fotlz/8FEGm4BbFMjJhJLf1vo23ZG+x5+k9VFRUEB4eDtQtQy96/HHs27aR/OE8lJFNr8Briojk8kee4fN/PMAXzzzK1U/8H5qguvk4Mo0Cn6Vpm5b+kd1j543V75HBKB4+fxaKRpa/+9PUqVNZvnw5AEuWNG2bjjNlitBhs7jwuLwom9nDdzYRSY7QaZTWOJi/IZ9VB8rZfLgal9dHlFFDVnww4QY1Zrub/HwbOwubPo69+kAFVpeXwalhoiig0CZkcjlxz/2LIzfcyJFb/kryxx+h8PqQ65r2++f1ePj2hTl4PW6uevxZ9CGhzY6huroam81GXFwc07Ons+SbJewO2k2uK5dwwpEkiZI5czB/+RVx//o/gvr1a/Y1QqJjuPyRp/nvo/fzv9dfZOK9DyGTyZAp5Phc3sYb+AOX18XM5TOxV+mQqyAmtG23PPjwww8BmDdvHrNmzWqTREd/bP8ym8WFKaLxTVDPVmK4Sug03lx5kJd/PoBBo+Khi7rz48xzWPfQGN69YSCv/qUfH908mO/uHnni+H9OqZufEB+iI9J4+h6bF37ax7T31vPx2sNtcg+CAKAwGEh8+y2U4WEcufEmlF4JeRM/rf/633kU7d/DJX+fhSni1EnATWE2m5k8eTJZWVn069sP+0o7Fz99MXcvv5vtJVsp/ddzVH34ETH/eIzgiRNbdA2A8IQkLrzjHg5sWMOGb74EwLapBPfRpi+NdnvdzPplFuuL1zM5+VI0LZic7S/Tpk1j+fLlVFS0/gaaSk3d74O7mQnh2Ub05AidRonFwYCUUN6ZNqBZ53126xASw06tJCtJElaXl+zHl4peHKHNKUNDSXz3XfL/eityj4t4c+NvnHlbNrJp8ULOm/pXErq3fBuD5ORk1q9ff9JjNreNO5fcypbp1zNwj5eYhx4i9JprWnyN49IGDGbQ5CtY9d8PSeqZjSregLuJ9V8sLgv3LL+HTaWb+M+5/0G7KY5ajf92Mm/MH3u8ABYtWkR4eDhhYa2zv9gfKY8NX7psnla/VkcmenKETqOspvEl3x6v78R/W50eFHIZscGnrz0ik8lwe3z4JLFJpxAYqqgokj/5GI/kJWvbaio//BDJ5zvtsS6HnZ/efZ2krD70u6jlvSv1URZX8PAnTvod8PHvKXIW95eatF1DUwy/8joik1P54a1XUEbqUKc0XvQwvyafqUumsrtyN2+d/xajkkbhcXtRtOEHkj/2ePXu3ZtXX32VxYsXt8nkY0etG4Ajuypb/VodmUhyhE6jKXVtqu3uk46PC9GibKB8fIW1bgJkmEhyhABRGAxUa3RUp/Sg5J/Pkn/LX3GXnNpb8dv8j7GZzZx/yx1+fZOVJInqL78ib9JkpIoqunzyKZmX3shzG5/jzmV3Um4/8z2U5AoF4267i/Ijh6k8ko+sgUnWkiSxcP9CLv/mcpxeJx9d9BEDYwYCoFDK8XpOnwS2huM9Xjk5OWzbto2ffvqJPn36tMm11bq6gZjo1JZXwT4biCRH6DTKa11EGBtORqptvyc5+VU2kk4zTPVHlceSHFH5WAgkMxKOtN4kvvMOzgMHOHjxJZS/9Ta+Y5WDq4oK2Pz9twy57GpCYmL9dl37zp0cufEmih5+GOOFF5L69SL02b25d8C9vDr6VXaU7+DSry/lm9xv8ElnllxEd0mj30UTqS0qR1Kevoco35LP3cvv5rHfHmNcyjgWTFhAl+AuJ55XaRR4zpI5KhJ1PyNjWMuqYJ8txJwcoVPw+SRqnR5e/Gk/8347hPHYMvHj/5q0KkxaJTXO38ev9xTVMCi14bHzSmvdUvIwvVhKLgSGJEkU+HxkuXwYRgynyzdfU/bqa5S9/DJV//0vEbfdym9Fh9AHh9D/okl+uaZ9504qP5iH5dtvUXftSsIbczGed95Jx5ybeC5fTfyKZ9c/y8OrHuajXR8xs99MhsYNbXFP0uBLryI/5xeKSw8SRfaJxysdlby9/W0+2/sZYdowXjjvBcYmjz3lfKVagcd5diQ5x+9TqRZ9FQ0RSY7QKcjlMt6ZNoCDZVZqHG4sdg81Djc1Dg/VNhf5lTYs9rrvjztYbmXasJQG262wupDLIEQXuBUbwtnN6fFRgJfB9ro3NUVICDGPPEzYdddS+uJL7P+/OexJj2dgfBdcOTkoevdGpmz+S7unrIzalSupXvAF9m3bUMbEEPP444Rcflm97YXrwnn+3Oe5rsd1PL/xeW776TbSQtK4OuNqLul6CXqVvlkxaHV6dAojuw/8RGrFCPJ8hXy25zOWHlqKSqHib73/xnWZ16FTnn7JtM6owuXwnhW1Y2w1db3MWtHL3CCR5AidxqiMKEZlNH6cJEk43D5qnG4iG5nDU1nrIjRIjVzeNlVMBeHPLHY3hfjQWD1IHh8yZd0nd3VKCgkvvsCOF+YQtHkDURu2cvj765AHB2MYPgxtZiaa9HTUXbqgMJmQ6/WgUCA5HPhqa3GXlOLctw/n/v3YNmzAsWMHyGTohw4h4dVXMJx3XpOTpT5Rffho/EesLVrLZ3s+45/r/8m/NvyLgTEDGZkwkgHRA0gNTkWtqP8NWZIkSgsKkSHD4q3iwZev55cuR4k3xHNH3zu4NO1SQrQhDcZxfANTS4WDsNjmJVgdTU2FA02QEo1OvI03RPx0Ogif14e5zE5VkQ17rQuX3Yvb6UGpVqDWKtAEqQiJDiI0JqjTf4I5UzKZDJ1aga4JP6cKq0tMOhYCyuJwsxcvMglchbVokn6faOq0Wdm7ZQODJ19BxuQrcOzYQe3KlVh/W0PtipX4bH/a20ihgD9t/qlKTESX1Yuw669DP3IkyhYuf5bJZAyNG8rQuKEU1Rbx4+Ef+bXgV57f+DwenweFTEGyKZmooCgMKgN6lR6Xz4XVbcXsNHPIcoj+pRnczw3kRBWQekTL1Te9xrDE4U2uXmwMr+vhqTkLkhxLuUMUAWwCkeS0U5JPoiy/hkM5FRzZWUF5fu3vqwZkoNYq6ybZub247F4kX90kNJkMQqKDSMwMI6VXBHHpISiaUQ5eOFmlSHKEADPbPezHh6SQ4cqvOSnJ2fXrcrxuN71GnY9MoUDXuze63r2JvPtuJEnCXVCI+8hhvJYafNZaJJcLucGA3GBAGR6OpmvXuh4eP4s1xDK151Sm9pyKzW1jb9Ve9lft50D1ASodldS6aimzl6FWqDGoDCSbkhkZP5Jhngwkp5L7r/oPH95/J1GFchTJTf/Qpg/RoFDKqSq2ktwr3O/31Z5Ul9gwRYhJx40RSU47Y691sXt1ETt+KaCmwoFapyQpM4z0gdGEx+kJizOgM6iQ/WH4RJIkXHYPVcU2KgutlBy2cHBLGduXHUUTpKT70Fh6nRNPSHTDK4mEU1VaXWJllRBQFocbDyCLDsJ1pAaG//7c7l+W06XfIAxhp76hy2Qy1AnxqBOatzGnvwWpgugb1Ze+UX0bPbZk5WZUyXrCklKITc9g1y8/kzF0RJOvJZfLiEwyUHqo6Vu3dEQ+n0TpkRoGXpQS6FDaPZHktBP2WhcbvjvErl8LAUgfEEX3qbHEpAWjaKCOC9S9mGmCVMR0CSamSzCZI+KQJImKAiv71heze3UR237OJ7V3BEOndCU0pnN34/pThdVFSoRIDoXAsRyr7aRND8GxvgTJKyFTyKitqqTowF7G33FPgCP0D6/FibvQimFEXVKWPng4v33+MW6HA5W26T0W0SnB5G0va60w24XKQisep1fUyGkCkeQEmNfrY9tP+Wz6/hAAAy5Koec5cejOsPdAJpMRkWAgIiGNQRNS2b+hhA3fHeK/T64nc0QcQyZ1QasXK4YaU2l1iuXjQkBZ7G6UchnGXhE4VhbgPGRG2zWEg5vXI5PLSe3bvG1M2iv77kqQg6573Zygrv0H88vH73E4ZytpA4c0uZ3oLia2LcvHanae2MSysyk+aEYmg8gkY6BDafdEkhNAVcVWfnp/F2X5tfQ6N56BF6eccXJzOkqVgh7D4ug2MIbtK46ycckhDm0rY8wNmST2aP09VjoqSZKosrrFlg5CQFkcHkw6Fep4I3KTGseuCrRdQ8jbspG4bj3QGZv+aV6SvFgs27BYcqi17sNq3Y/bXYnHU4PXa0Mu16BUGFGqTAQFpWLQd8Ng6EFIyECUSkMr3iU4dlWgTg5GHlT34SssLp7QuATytmxsVpKT0D0UmQwO76ggc3hca4UbUIdzyolNC0GtFW/hjRE/oQDZs6aIlZ/uxRCm5bIH+hPdhL1azpRCJafv+UmkD4jm53m7+OalrfQZm8jQS9PEEunTqLK5cXl9RJs656dBoWOw2N2YtEpkchlBWRHYtpZhujCFov176TXq/EbP9/k8VFQso6T0eyoqfsHjqUYmU6PXd0WvTyfY1Ael0ohCocfnc+Lx1OB2V2G1HaSiYgUeTw0ymZrQkIFERI4lJnoSKlWwX+/RY3bi2F9FyMSuJz0en5FJ0f49zWpLZ1AT0zWYvG3lnTLJcTu95O+pYsikLo0fLIgkp61JksS6bw6y6fvD9BgWy8iruqHStO2Sb0Oohol392Hbsnx++yqX6lI7427u2eZxtHfF5rqS+dEmsYJBCByLw43pWDFK/eBYalcXUrUuD2t1FTFp9ReGcrurOVrwCQUF/8XpLMJg6EFC/F+IiBiF0ZiFXN74cLUkSdjth6moWEl5xXL273+GAwf+j5joiSQm3ojB0M0v92jbUIxMKSeoT9RJj8emZ7BzxU+4HHbU2qYvl07NjmTdtwdxOTydrrfjyK4KvG4fKdkRgQ6lQ+hc//fbOZ/Xx88f7mbfuhKGXtqVvucntclutacjk8voMzaJ0Bg9S9/ewcJ/b2bi3X3QGsQ8neOKLXYAYurZpVwQ2oLF7sGkrfu7VEUFoU4NpnZNEQCxaacmGT6fk/yjH3Ho0Ov4fE5ioicSn3AtJmOvZl9bJpMRFJRCUFAKN9/8CUVFCrxeMyrVa9z+t08495xr6dLl72g00S2+P8nrw7q+mKA+Ucj/lJDEpmcgST5KDh4gMTOrSe35fD4i09XY5WUs/uJHQuI0OBwOPB4PGo0GjUaDXq8nMjKSqKgogoI61sKC3auLiEo2EhLVseIOFJHktBHJJ7H84z3s31DKuFt6kj6g5S8K/pTcK5wp9/Xj25e38u0rW5n0974ndrc92xWbnchlNFoVWRBaU11Pzu9/k8bhcbg+NhMX2g19SOhJx1ZVrWf37lk4nAXExV1FauoMNGr/fOKfP38+ISEhAHz55QIeffReMjN/pLjkW7p2vZfEhGnIZM2vyWXbXIrX4kI/9NShpbC4eJDJqCoqbDDJqampYf/+/ezbt4+8vDycTieEQs4BBaYyAxqNBqVSicvlwuFwYLPZ8Pnq6o6FhISQnp5Oeno6qampqFTt94OepdzO4Z0VjLque6BD6TDEu1kbkCSJXxfsZ8/aYs6/MbPdJDjHRSYamXB3Hxb9ZwuLX9vGhLv7oBJVkyk224k0alA2soRfEFqTxe4mPuT3oRptZjh2tY2skBFIkoRMJsPnc3Lw4IscPvI2wcH96d37bfT6NL/GcTzBAaipsaJWhzF0yDIO5r3A/v1PU16+jMwe/0Krbfou6JLHh+XnI+iyI1CfpkKxQqnCGBaBpazk1HMliYMHD7Jhwwb27t0LQEJCAsOGDSMuLg5XhYrlH+RyxbSBpyy19nq9VFRUUFJSQn5+Pvv27WPDhg3odDr69u3LgAEDCGth5efWtPPXQtQaRbt7D2nPRJLTBnasLCBn+VHO/UsG3QbFBDqc04pMNDLhrt58/eIWVnyyh7E3ZAZsKK29KLY4iBHzcYQAO7666jiZXMYh+R560A/n/mrkKRLbc27DYsmha5f7SE7+KzJZ63xImTp1KsuXLwdgyZIlqFQmMrr9g4iIMeze9QDrN0ykd/abBAf3a1J71nVFeM1OTGPrH0ozRUZhLj05yTlw4AA//vgjJSUlREZGctFFF9GzZ8+Thp58XSW2fl/MxiV5XHxH75POVygUREVFERUVRVZWFuPHj6esrIwtW7awefNmfvvtN7KyshgzZsxJyV0gOWrd5Kw8Ss8RcWL+ZDOIJKeVFR80s2rBfrJGJdDrnMBWHm1MTJdgRl3XnR/f20Vsl2B6nZsQ6JACqsjsEPNxhIA7vrrqjwpq9pJsyqD4f79SOOBFPN4a+vf7L8HBjVcVPhMffvghAPPmzWPWrFksWbIEgPCwEQwatJjtObezecu1ZGb+m+ioixpsy2txYv7hMPoBMagamF9iCAvHWl0FQEVFBUuWLCE3N5ekpCSmTZtGSkrKaT+QyeUyBl6Swo/v7qL4oJmYLvWvCJPJZERFRXHBBRcwatQotm3bxooVK9i1axdDhw7l3HPPDfgw1pYfjyBJ0O+C5IDG0dGIfvhW5LS5Wfr2DqKSjQy/zL9dx62l26AYss5L4Nf5+yk7UhPocAKqRPTkCAEmSRIWh5tg3clvsG6nk4qu+zjU7TEku4+BA75s9QTnj6ZNm8by5cupqKg48ZhaHUbfPh8SGTGOHTvuoqjoywbbqP46F5lKTvD4lAaPU2m0uJ1ONm7cyBtvvEFlZSVXXXUVN954I6mpqQ32OKf3jyYsTs/aRblIktSke1Or1QwcOJC7776bESNGsHbtWt566y2KioqadH5rsFY72b48n96jEtAZRd2u5hBJTiv6bWEuTruHcbf0QqHsOD/q4ZenERqrZ9lHu/F5fYEOJ2Aqal1EiEnHQgA53D7cXumk4SoAlNXYY95HrQon4ZdZyMtCWjWO6upqCgsLT3y/aNEiwsPDT5m3olBo6NnzBeLirmLX7gcpLf3faduzbS3FvrOCkIldTxT/q4/b5eKIR8bixYvJzs7m9ttvp0ePHk0aTpfJZQy7LI2CfdXsW1fchDv9nUajYdSoUdx6660oFArefvtt1q1b16w2/OWXz/eh0irpc35SQK7fkXWcd94OpnB/Fbt+LWTo5K4YwzpWb4BCKWfUdd2pOFrLtp+PBjqcNlPr9OD0eIG6DfCqbC5CRbVjIYAsjrp9q44vIQdwu6tIGLULGSr6DfkEXUwclZ/sxlvrarU4zGYzkydPJisri969e/Pqq6+yePHi0yYaMpmc7hlPER19MTt2/p3KqjUnPe8usVL11X50fSLRZTW88stisbC5sBSnWsc111zDhAkTUKub9zeZ3DOc9IHRrFpwAHtN839GUVFR3HLLLQwaNIjvv/+e77///sTKrLZwcGsZB7eUMfLKdLEVTwuIOTmtwOeTWPnffcR0MbX7eTj1iU4xkT0qkfXfHqTb4OhOuwfMcV6fxLBnf8bq8pISHkRqhAGfhNjSQQio45tzHl9CLkleduyciVzlQ1t7E1p9DKq/hFLy8hYq/7uHiJt6IWuF1YDJycmsX7++ycfLZAoyezyH21XJjh13M2jgN2i1sfgcHio+3o0iVEvopekN9sZUVFQwb948FFod2oO7yMiov/BhY0Zckc6nT6xlxSd7ufC2Xs1eVKFUKrnwwgsJDw9nyZIlmM1mrrjiChSK1p0AbDU7WfnpXlKywknrH9X4CcIpRE9OKziwsYTKQivDr0hH1oG3Sxh4SQoKlZxN/zsc6FBaXYXVicXh4aqBiYxMj8Tm8tAlUk+PWLHLrxA4f+7Jyct7lcrKVZRu6IHXUbfkWhGsIewv3XHmWahcsA/J17S5J61NLlfRs+eLyOUacnbchcdhp/yDnXhr3IRf1wN5A2UqqqurmTdvHmq1mt7RYcQnnNkiiCCTmtHX9+Dg1jK2/Hikxe0MHDiQq6++mv3797Nw4cJW7dHxen388M5OkMF513U/61e7tpRIcvzM5/WxfnEeKVnhxKT6d3+XtqYJUtFnbBI7fy2gptIR6HBaVfmxbuwr+ifw+MSefPrXISy79zxSIk6t3SEIbcVi9wBg0qkwm7eQd+gVuqTOwGOOxe38/W9S2zWEsKszsG8ro/rrA02eZNva1OowsrJeo6ZmB7uXPIW7sJaIm3qiiqx/NVVtbS0ffvghcrmcqVOnInO7UGrOvCe5S59I+l2QxNqFueTvqWxxOxkZGVx22WXs3LmTxYsXt9rPes1XuRTnmrngr706fU96axJJjp8d2FyKudTOoAmdY/O07NEJqDVKtp7Bp5+OoLzWCSAmGgvtyvGeHINaYvee2RiNvUhJ+RtBpmBs5uqTjg3KjiT0snSs64qpWrAPydM+Fg0YVT2JrJhMqekLdFdr0STV3zvq9XqZP38+LpeLqVOnYjKZsJmrCTL65wPj4IldSOgRxvdzcyjJs7S4nczMTCZNmsTmzZtbZTLypv8dYtvP+Qy/Ip24tBC/t382EUmOn+38pZD4biFEJhkDHYpfqLVKMkfEsWdtMW6XN9DhtJrjSU6kUSQ5QvthsbtRKWSUFr2HzXaQHt2fRSZTEBwVjfk0VYD1A2IIuzoD27Yyyt/bgc/mDkDUv/NUOiidu42QXePRqRM5aJ+DJNWffP30008cPXqUK6644sTKLXNZCaYo/1T4lSvkjL8ti/B4A9++spWKgtoWt9WnTx+GDh3KDz/8wJEj/vsQmLPiKGsXHWTgxSlkjzq7a5X5g0hy/Kiy0Erh/mp6dtDJxvXJHBGHy+HhwMZTX1Q7i4paFwaNEq1KVBIV2g+Lw0OswcHhI2+QmHADRmMPoK4KsKX09H+PQX2iiLwlC3exlZKXt+DMM7dlyCfYtpdR8soWJI+PmNsH0j3raczmzZSV/XDa4/fu3cuaNWs4//zzSU6uK3jn83mpKS8jONJ/2xioNAouuTMbY7iWhf/eTMG+qha3NXbsWBISEliwYAF2u/2M4pIkiQ3f5fHLZ/voPSaRgZeknlF7Qh2R5PjR7jVF6IwquvSJDHQofhUcqSOpRxi7VweuGFZrK691EmEQK6mE9sVidzMu5UdATkrK7SceD4mJw1pdhcN6+p4ITWowUXf2RRGioeyt7VR/n4evjXpivVY3lZ/vpfLTPWjTQoi6ow+qyCDCQocSFjqCg3kvIkknx+JwOFi8eDFpaWkMGTLkxOPm0hJ8Xi8h0f7dDkcTpGLyzL5EJBr55qWt7G1mDZ3jFAoFl19+OS6Xix9//LHF8Xg9PpZ9uJv13+YxeGIqwy9PExON/UQsIfcTSZI4uLWM1D6RHarwX1OlDYhi2Ud7sFlcBJk6djJw0wcb2FtcQ7BORaheRYhOze4ii5iPI7Q7DmcpwyKXk5Q4HZXq9x3Ho7vUVVAvyT1Acnaf056rDNMSeWs2Nb8cxfLjYWxbSgk+P5mg/tGtsupTcnupWV1IzfJ8AEKv6EZQv6iT3qy7dJnJxk2XUVLyHTExE088/vPPP+NwOLjkkktOOr54f93Gm9Fd0/0eryZIxYS7erPikz389P4uCvZVMeKKdNTa5r0tmkwmxo4dy3fffUd2djYpKSnNOr+y0MqP7++kstDK2BszyRjcPvc37Kg637txgFQV2bCU2UnNbri4VUeVcqxo16Gc8gBHcmZyy2pZtqeUQalh9EsOISRIjdnuRqdWMK6n2NlXaF8i5P9DQk5i4k0nPR4WG48mSE/Rgb0Nni+TyzCdl0jMvQPQpAZT9eV+Sv6ziZpVBfiOrdw6U16LE/OPhyn610YsPxxG3z+amPsHoO8ffUpvRHBwH8LCRpJ/9IMTjxUXF7NhwwZGjx59ymaYRQf2ERITi87YOqUcFEo5o6f2YNR13dm/sZTPn17P0RasvOrfvz+JiYksWbKkycvKvR4fW386wvxnN+B1+7h81gCR4LQC0ZPjJ4dyylGq5SR0D2384A5IZ1QT2yWYQ9vLyRweF+hwWmzpzmJ0KgX/nJKFroE6HYIQaD6fh2TdTxx1jEClOvlNXiaXE5PWjcK9u5rUljJMS/g13XGNiKfm16OYl+RhWXoIbY8wtBlhaDNCUTRjuNZT7cCxpxLHnioc+6qQKWUE9Y3CMDIBVYSuwXMT4q9le850LDU7MBl7sWLFCkJDQxk0aNApxxbu201sWsuLADaFTCYjc0Qccd1CWDZvN1+/uJXkrHCGTUkjLK5pJSTkcjnjxo3j3XffZefOnWRlZdV7rCRJHNxSxpqFuVjK7WSdl8DQKV1RitejViGSHD8pyjUT2zUYZSeeuBqfEcrOXwuQJKnDjhcv3VHMqO6RIsER2r2KypXolZWU2sef9vmU7L6s/vxj3A4HKm3Tto5RJxoJ/0sPvBYX1o3F2HdVULVgHwCKMC2q6CBU0UHIg1TItApkKgWSy4vk8OCtdeMuseEutuKzuEAuQ5NiIuTiVIL6RyNv4jBPePgoNJoYCgo+pdZ0J3v27GHy5MmnVA+urayg5OAB+o2fWE9L/hUSFcSU+/qRu7mMNQsP8N+n1pGSFUHWufEk9ghrdIgvMTGR9PR0VqxYQWZm5in343J42LeumJyVBVQWWknqGcb46XUrvYTWI5IcP5AkiZI8Mz1Hdq5VVX8WnWpi45JD1FQ4MDXyaa09Kqi2s+2omZtGiFULQvtXUvItxbZEZKrup32+64DBrPz4PQ7lbCF94NBmta0wqTGNTsI0OglvjQvHgWrchbW4S2zYtpbhs3uQXF6QABnINEoUeiXKqCD0/aNRxRnQpoc0ObH5I7lcSWzMpRwt+ISc7VmEh4eTnZ19ynG5m9Yjk8tJ7Tew2ddoKZlMRlr/KFKzI9iztoiclQV8+8o2jGFaUrIjSM4KJy49BFU9H5JGjRrFW2+9xZ49e+jZsydWs5MjOys5vKOcIzsr8bi8pPaO5JyruhGf0Tl7/dsbkeT4QU2FA3uNm6iUttsCYNy4cRQXFyOXyzEajbz88sv07du3Va8Zfez+SvIsHTLJ2XqkGoDkcFHFWGjffD43FRUr2F5+LknJp9+UMTQ2nrD4RA6sX9PsJOePFEY1+r5R0PfkvZEkn4Tk8SFTyf3ecxsZeT6HDr9OYdGvDB0yDbn81OmhBzauJb57JjpD29ccU6jk9BwZT+aIOIpzzezbUMKh7eXkrDgKsroVp+FxBgyhGtQ6JWqdEp/Xh8vhxaSN4PuFy1k3rwq7xQWyutfOfhckkTEktsNt2NzRiSTHDyqLrABEJLRdt+P8+fNPTNJbuHAhN9xwA9u2bWvVa+qMavQhmhP329Gc0y2C2GAtL/20j/dvPHX8XxDai+rq9Xg8NawvyqRXRv0v092Hn8P6r79g9I23oQnyb/Iuk8uQtdKwrtHYCwghPDz/tL04lvIyDm/bwpibbz/15DYkk8mITQshNi0E6WqJyiIrJXkWKgutVBTUcnSvDZfdg9PuQa6QodEpMWjiKfRuo99AA0ld4ohLD+nwK1I7MpHk+EFNhQO5QoYhpO2WIP9xFYLZbG6zOTKmCC2WijMrehUoRq2K8b1iWban8xY1FDqHispfUamjyDPHY9SevicHIGvUONZ88V92/7qCPhdc3HYBnjEZlZUJREeXotOd2iucs+wHlBoNPUacG4DYTk8mkxEeZyA8ruEPs263m3//ey9SWAVp/fu0TXBCvZq1hHzu3LlkZ2djMpkwmUwMHTqU77///sTzubm5TJkyhcjISEwmE1deeSUlJQ2/oTTWJtQtMbz++uuJiYlBr9fTr18/vvzyy+aE3qos5XaMYdo233F86tSpJCYm8uijj/LRRx+1yTWN4VpqyjveZp2F1Xb+u/4IRypttJNNmgWhXhbLNnT6PoAMk67+z6KGsHDSBgxh6w/ftZtNOZuirKyMsjITCkUZHk/NSc95PW52LFtK5sjzUOvq38izvVKpVGRkZLBnz55AhyLQzCQnISGBOXPmsGnTJjZu3Mjo0aOZNGkSO3fuxGq1Mm7cOGQyGcuWLWP16tW4XC4mTJjQYN2Ahto8burUqezdu5dvvvmGnJwcLr30Uq688kq2bNnS8jv3o9pqJ4YAjLN++OGH5Ofn8/TTTzNr1qw2uaYxVEtNVcdLct5Ymcvsr3L4aXcJ8SEdbz6RcPbw+TxYLDkoND0BMGjq78kB6HfRRCqOHuHA+jVtEZ5f7N27F4c9GpCwWLaf9FzOsh+pra6i74UTAhOcH2RkZFBWVkZlZct3Oxf8o1lJzoQJE7joootIT0+nW7duPPPMMxgMBtauXcvq1as5dOgQH3zwAVlZWWRlZTFv3jw2btzIsmXLWtTmcb/99ht33XUXgwYNokuXLjzyyCOEhISwadOmlt+5H7kdXtTawC1JnjZtGsuXL6eioqLVr6XWKXE7O95GnWU1TkamR7DziQv48GYxH0dov2y2XHw+Oz5F3T5VBk3DswoSevQiObsvq+d/jM/Xsr/NcePGkZ2dTZ8+fRg5cmSrf4Dct28fcXH9UCgMWCw5Jx53u5ys++ozegw/l/CEpFaNoTV17doVhULBvn37Ah3KWa/FFY+9Xi+fffYZVquVoUOH4nQ6kclkaDS/z0vRarXI5XJWrVrVojaPGzZsGJ9//jmVlZX4fD4+++wzHA4H5513Xr1tOZ1OLBbLSV+txePyotK0XZJTXV1NYWHhie8XLVpEeHj4iV17W5NSLcfjbFpFz/akotZFhEGDXqNEpRCFvoX2y24/DICDuh2ojU1Ypj38yuuoOHqE3b+uaNE158+fz/bt29m6dSv33HMPN9xwQ4vaaQqPx0NhYSEpKV0ICko5cb8AW5d+h9VczdDLr2m167cFjUZDXFwc+fn5gQ7lrNfsicc5OTkMHToUh8OBwWBg4cKFZGZmEhkZiV6vZ9asWfzzn/9EkiQefPBBvF4vRUUNb+xYX5vHzZ8/n6uuuorw8HCUSiVBQUEsXLiQtLS0ett89tlneeKJJ5p7ey3idnrbtFql2WzmiiuuwG63I5fLiYyMZPHixWc0+djrcVNZWEB5/mEqC47itNbisttwu1yotVrUuiB0RhOHdki4nSqcdhcaXcdZMVBudZKdEBzoMJrF55OQt/E8LyHw7PajyOVaal11JRsa68kBiE3PoNvQkaz8+D269BvY7G0Q2nIhQ3FxMV6vl4SEBCqrErA7jgJgKStlzYJP6X3+RYTGdvyaYwkJCeza1bSK1ELraXaSk5GRwdatWzGbzXzxxRdMmzaNlStXkpmZyYIFC7j99tt5+eWXkcvlXHPNNfTr1++0NRCa2ibAo48+SnV1NT/99BMREREsWrSIK6+8kl9//bXe8tmzZ8/mnnvuOfG9xWIhMTGxubfbJDK5DKkNZ7MmJyezfv36M27HXFpC7qb15G3ZQP6uHLxuNwD6kFB0RhPqID1KtZqa8lKcNhu2P+x6/Pbf5pPcux9d+g6gS/9BAall0Rx55VbC+necpGx3kYVJr65Gr1EQbdISE6wlNlhb99/Hvo8J1hJr0mHSKTtsBWrhVHbHUbTaBCqO7Rqub0KSAzD6hlt5f+Z0Vn70Hhf+7e/Nvu7UqVNZvnw5AEuWLGn2+U1VUFCAQqEgJiYGuyOBstIfkCSJn955DY3BwMhrpvr9moGoKxYfH8+aNWuora3FYBBVjQOl2UmOWq0+0YPSv39/NmzYwEsvvcSbb77JuHHjyM3Npby8HKVSSUhICDExMXTp0qXFbebm5vLqq6+yY8cOevasm4jXu3dvfv31V1577TXeeOON07ap0WhOGjprTSqNArerY8xT8fm85G3ZxNYfvuPQ1k3IFUoSMnsx8pppRHdNJyIxGa3+9H+QkiSxYfFONizeSN+xKg5u3sj/Xn8BhUpF92Hn0GfcxcSkdWvjO2pckdmOJIFe3XEqJuwrqcHl9fG3YV2pqHVRZHawo8DCj7tKqbA6+eNCGrVSToReTYRRQ6RBQ4RBQ4RRTWiQGr1GWfelVqDXKDFolASpFRiOPR6kVogEqZ1xuytRq8OptbvRKOWolU0bXtWHhHLOdTfy41uvkjZwCGkDhzTruh9++CEA8+bNY9asWa2W6JSXl5/olVerI3C5K8lZ9gN5Wzcx6f5HW2VFlb/qinl8EvttDvZY676KnW5qPF5qvF6UMhkGhQKTUk6yTkOSpq5uUVlZmUhyAuiMX/V9Ph9Op/OkxyIi6nasXrZsGaWlpUyc2Ly9R/7Yps1mAzilN0ihUDR5t9fWplQr8LjaRyz1kSSJg5s38Msn71NZkE90l3QuuP3vdBs8rMkvKjKZDLnCgM7UlWFXjGTYFddira5i58qf2fbjEnau/JmkrD6ce91NRKU0nNi2pcLquro+g1Jbf85SS1TbXHyy7gjRJi2pEUGkhOspq3GiUymYMSb9lCTE7fVRWuOk2Gyn2OykrMZBea2L8lon5bVO9pTUUH7Aidnuxury0NDKYpkMglR/SIA0CvRq5YkkSH/s+xP/few4vbru2OPHpYbrxdCan3i9dhSKIGqdnibNx/mjrNEXkLdlE9+/9h+ue/aFFg37TJs2jenTp1NRUUF4eHizz29MVVUVoaF1Wxoo5EF4vXaWvf8G2WMuJG3AYL9fD85sOM7i8fJ9mZmfKy2sqLRg8dS91sdqVMRrVBiVCkJVSryShNnj4bDDy7dl1Vidbv4K3LNpFxluFePCTZwTakQp/k7aVLP+gmbPns348eNJSkqipqaGTz/9lBUrVrB06VIA3n//fXr06EFkZCRr1qxhxowZzJw5k4yM33eRHTNmDFOmTOHOO+9sUpvdu3cnLS2N2267jeeff57w8HAWLVrEjz/+yOLFi/31czgjmiAl5tL2WyCvoiCfn995nfxdOST1yuaC6TOI63b6/XAa47S5Uf+hboc+JJRBky5nwIQp5G5Yx6+ffchHD86g5zmjOff6m5s9N6A1VNS6AIg0tl2xxub4cVcJzy3de9JjCrmMuBDtaV+MVQo58SG6Ji2F9/kk7G4vVpcHq9OL1emh1unB5vJQe+z7uq+6Y2qdHmzOuufKapwcqvjD804PVpfntHWGJvaO4+VrWrf7/2zh89pRqoKpcXqaNB/nj2QyGRf+7e988tBMvvnPs1zz5L8a/RBTXV2NzWYjLi4OaP2FDNXV1XTt2hUAu7Uc8BKZksCoG25tlesd19zhuF21dt4vKOeL4irsPh99jEHcmhDF8FADPfRaQlT1/7+RJIkip5v3N/9MLzwsrbDwQUE58RoV18eFc21cOJHqhksDCP7RrL+g0tJSpk6dSlFREcHBwWRnZ7N06VLOP/98oK72wezZs6msrCQlJYWHH36YmTNnntTG8eGsprapUqlYsmQJDz74IBMmTKC2tpa0tDTmzZvHRRdddKb37xfGMC1Hd7e/egiSJLF16WJ++fh9jBGRTHnwH6T2GXBGwxOWCgem8FNrAsnlCtIHD6NL/0HkLPuB1Z99yKHtW7hw+gxS+vQ/k9s4YxVWFzIZhAa1zzk5FVYXRq2SdQ+N4XCFjbxyK3nlVrpEnHmZfrlcdmLICj9Mm5IkCYfbR+2x5KjW6eGln/ez6XDVmTcuAODzuZDL1NQ6PBhasAGmJkjPxHse4r+PPcCifz3FlNmPo1LXn+C3xkKGhtTU1GAymXBYa9m7cQG6WBh3+y0o1a3799nU4bg8m5OnDxbyXZmZGLWKO5Oi+EtcGLGapscnk8mI06qJDAkhWgVPDulBTq2dDwrKeelwCS8dLuG2xCjuTIrCoAxc+ZGzQbP+gt59990Gn58zZw5z5sxp8JhDhw41q02A9PT0dlXh+M+M4VqsZhdetw+Fqn0sT3bZbXz38nMc3LyBPhdczDnX3ohKc+YFC2sqHEQm1f9uqVAq6TPuIroOGMTSuS/x5bP/YODEyxh5zTRkjUxAby0VtU7CgtQo2mk3cUWtkwiDhiC1kh6xJnrEBr73qz4ymQydWoFOrTjRM5YSHkRuWW2AI+s85AotXp+D2hb05BwXkZTClAf/wZfPPMa3/3mWSfc9jEJ5+p4Dfy1kaApJknC5XCjlchbOeQKfXo0uFsJje7TJ9aH+4Ti718f/5RXx7tFyItVKXuqexKXRoajO4HVDrVbjdruRyWRkG4P4T/ckHusax9z8Mt7IL+Wjwgoe6xrHlTGhYm5cK+k4MzHbseBjO3Kby+2ExQZ+h+uainIW/t8TmEtLmDLrH3TpN9Av7UqShLnMTtd+kY0eawyL4LLZT7Dpu0Ws/OR9qkuKGH/nvQ1+omyJapuLJxfvQimXYdKqCNapMOlUhOnVGLV180f2l9YSbmifvThwvIZP+42vMQ63D634NOo3CoUOn9dW15PTSLXjhiR078mk+x5m0b+e5Ktn/8GEex6qd1FBW/F4PEiSxObFC3EfPcSYv19ESfW7yOWt9/vflOG47TU27th1mHyHi/tTY/hrQiQ6P9TTOp7k/FGISsnsLrFMjQvnnweLmLHnCD9UmPlXt0TCO9DiiI5C/ET9IPzY7uNlhy0BT3KqigqY/+RDyGRyrnnyX0QkpfitbXOpHZfdQ0Ri08Y9ZHI5AyZcSkhsPN+9/C8WPPUwl81+Ek3Qma+eqHG4eXrxbootDlbuK6NXvAmby4vF7sZsd+P2njxx5LyMxhOz1lBe6+TFn/ahVigICVIRElSXiB3/CglSU2R2EK5vn/OFmsLh9qJpJz2YnYFCHoTLVUmN03PGW5Ck9O7H5Q8/zdfPP81njz3AlFmPERwV46dIm6/kcB4Aztoarnl8Dnb5TyhqWndLnMaG4z4qLGf2vqP00OtYOiCDDL3/4mmo4nG8Vs1rmcmMjwjm/r35jN6wh3lZXehj6nj7dbVnIsnxA61eRUh0ECV5FjKGxAYsDkt5KQueegS1VscVj/0TQ6h/Jw6WHKqrGh2d0rzhlLQBg7nqsWf54plHWfTck1w6+4kz7tHZlm/m8435dI8xMjI9gg9uHHRiOEqSJCyOujkjtmMTbhPDAvPCsbvIwsdrjxAfosPp8WG2u05JwACmDU0OQHT+4fCInhx/UmsiMJs3H+vJOfOX6ITMXlzz9PN8NedxPpo1gzE3306PEeedeaDNIEkS235YwopPPoAuPRl+9VSiU7uyd9/HqNVRrXrt+objfJLEMweLeO1IKTfGR/BEWhxqPw+pK5VKPB5Pg8dcEhXCgGA9N+3IY8qWA7zRM5kLIjpW4dL2TCQ5fhKdaqI4r/W2jmiMzVzNF08/glwh5/JHn/Z7ggNQkmchJDoIrb75Xegxad2YMusffPHPR/n82acpGXwNpiAtIUEqQoPUhOpVBOvUhB7r6VA20lVcaatbMbVg+lCM2pPjkclkJ3pKWlNBtZ0QnarBYm2xwXWfCv9zZW8GdwlHkupWO1Xb6nqcjn/1Tw5t1Vhbk8vjRakQ8wn8RadNxOEsxOp0tWji8emExSVw3bMv8vO7c1nyyvPkblzHeVNvwRDm/yXif2YuLebnd+eSt3UT2WPHs7qgDMWxGmYORwE6XUKrx/BnXklixu4jfFlSxVNp8fw1sXV6epOTk1E3YUJ1jEbFl33SuHP3YW7IyeOF7olcHdv6/2/OBiLJ8ZP4bqHsXVeMzeIiyNS28yt8Xi+LX/oXTpuNa556HmNYhN+vIUkSh3dWkNC95W/G8d0zmXTfI3z5z3+wucDH1piRWOspomjSKo8VtdMQGlQ3xyYkqC4JCglSs+VINWqF3C+fdFvqyjfWIJfDq9f0o3diyGmPiQ2uG24oMtft3C6TyQhSKwlSK4nrJLuhxwbr+GVfWaDD6DS0ugQkyYNCKseg8V8Pn1Zv4OK776dL/0Ese/9N3v37rQy45FIGTrwUtdb/v4v22hrWffU5W5cuRmc0nZgfuPapp07MU7Hb8wkNaZ3aOPWRJIkH9x3lq5Iq3uiZzKSo1vuA4XK5mlwIUKeQ83bPFB7cd5R79uQTpFAwMSqk1WI7W4gkx09SssKRAYdyyskcHtem1171+Ucc3b2DKx59hpDo1hlvryqyYSmzk3pl+hm1k5Ldl6ARk+j360Ieu2k8qQOGUW13UW1zU2V1UW13U21zUWVzU17jpKzWSZXNzc5CC1U2F9VWNzXOuu7frpH6gK1I8Pkkisx2gtRKLn/jN2Zd2J2bR6SeEo9eoyRYp6Kguv3WUTpT3aKNfLjmEA63F61KDFudqSBdKgDBqnyMWv8nAD2Gn0tqn/6sX7SADd98wdb/fUvP88bSe9xFhMac+WtX+ZFDbP1hCbt+ratJM/jSqxhw8RRU2rpeTZ1Oh81mw+dzYbcfIj7uqjO+ZnM8fbCIjworeKl7UqsmOAB2ux2ttulzfOQyGXO6JWD1+vjbrkMYFF0YHd749ACXx8fB8lryK+3UOt3UODz4fBIGrQqjVklssJa0KANBZ+HE5rPvjluJzqgmpmswedvaNsk5tHUTG77+gnOuu4nEzNPv4+UPedvLUGoUZ9STc1zCyAv5bvN2ls59iRv+3Y2oiCiijE1/IXB5fFTbXQH9g61x1BXFe2ZKL3YWWnj6u938llvB81f0Jkx/ck9ebLCWInNnTnIM+CQ4WGYlM679Ln/vKHS6JJTKEBKNea3WU6nVGzjn2hvpc8HFbPnfYnYs/5FN3y0irlsPuvQbSGrfAUQkJSOXN560ej0eSg/lcnDzRvK2bKDk4AGCgkPof/Ek+oy7GH3Iya8ZISEhVFdXU1u7B5/PhcnUu1Xu8XQWllTx2pFSnkiL46rY1q2ALkkS1dXVJ1Vbbgq5TMaL3ZMwe7xM33WIHwZkkKI7eQ6j3eVlzcFylu0pZX1eJQfLrHj+UKVTpZAhk8lweX6vxC+TQVJYEP2TQhnVPYpzukW2+pB+eyCSHD/q2jeK37460GZDVi6HnR/feY2kXr0ZcMmUVruOJEnsXVtMSlY4Sj98Uo8waPk54jyyzAv5+d25TH7gsWb1yKiV8mYlRa2h2n6sirJBw0MX9WBIlzDunb+Ni176ldeu7Uv/5N9fQDVKObYOsrdZS6RH1622219aI5IcP5DJZOj0WXQJPtzqw7GmiCjOve4mhl15LfvWrOLAhrWsW7SAVZ99iFKlJiwhkYiEJHQmE2pdECqNFpfDgctuw2aupiL/MJWFR/F6PGj0elKy+zFw4mWkDRxSb12e0NBQqqqqMFu2IpOpMBgyW/Uej9tda+eePflcHh3KrQmtv9qytrYWj8dzYguL5lDJZbzWI4kLNu3j5h15LO7XDZ1Czvaj1Xy05jDfbi/E4faRFBbEiPQIpg5NISPGSHJ4ECatCo1SfiLJqXG4Kai2s6e4hj1FNfyWW85XWwpQyGWM7h7F1KHJjEiL6LR1ekSS40cZQ2JYszCXPWuK6HdB66+W+W3+x9jMZq545JlW/QUt3F9NVbGNc67JaPzgJog0qnHL1SRcdC0HPn2FvWt+pfuwc/zSdlupstXNKQg5VkV5dPdolswYyV2fbuHqt9byxMRe/GVwEm//cpBtR81M7tv8PYQ6imCdimiThn0lNYEOpdNQabPoGvw+bVVZQKXW0PPcMfQ8dwwet5uifbspPZRHef4hKguOUpy7H5fdhtvpRKXVognSozUYiE3vTtaYC4hK6UpsegZyReMfgkJDQ8nLy6O6+jBGYyYKRevfpNPn47adh0nRqflXRmKbvKFXVtZVwW9uT85xwSol7/VK5eJN+7hj1T6qd1aw+Ug18SE67hyVxoW9Yhsdslcr5YQbNIQbNGQn/B5HYbWdn3aX8Om6I1z/7nq6ROq55/xuXJwV2+mSHZHk+JFWryJtQBQ7fy2g7/lJyFqxwm5l4VE2L/mWEddMJSSmdZet7/ylgJDoIOK7hfilvWhTXS/MVnkCfQcNY+WH79B1wGC/FwpsTdXHVneFBP3+aTU2WMenfx3CU4t38dDCHPaV1DB/Yz4AY3tEByTOttIt2si+ElH12G+0wwhSvY7WtwNo27o2SpWKxJ7ZJPbMbpX2Y2NjsVrNVJT/QlLyza1yjT975XApB+0OfhyQQZAfivw1RUFBAUqlksjIlvca6Rw+0vfUsizvKF1jjbx1fX/G9Ig+4+rtcSE6pg5N4fohyWw4VMXcFQe489MtvJOYx6OXZHbo1Z5/Jip4+VnWuQlYyh0c2Fzaqtf5bcGn6MPC6De+eTu8N1d1qY0Dm8vodW683zJ8o1ZFRrQRm9PLyL9Mw2quZvuP//NL222l+lhPzp/3w1Ir5Tw1uRdPT+7Fh2sOYXN5+fzWIQGr09NW0qOM7Bc9OX7jIJ1KRzA+x6+BDsXv4uPjCQ4uxeurJTJiTKtfb5/VwcuHS7grKZoehrZb0VhQUEBsbCyKJvRu/ZkkSXy09jDjX/oFW7WTuMExOAdHcG6PKL9uTyOTyRiUGsb7Nw7i01sG4/H5uPyN3/i//+05aT5PRyaSHD+LTjWR3Cuc9d/m4fO2zi9J2ZFD7F3zK0MvvbrVN7Xb8F0eQUYVPUf4dzK1TAY6tYLQ2Hh6njuG9V8vwO1w+PUaranK5kKtlKOtp9LvdUOSeev6AVyUFUOfpJC2DS4AMmIMHK604XB33rlHbanG4WFbWRZ2y89IUud4sznOZDIRG1eEJIW2yXycJw4UEq9VMSO57XpTJUkiPz+fhITm1wAy29zc9MEGHl20g8v7J/DDzHN45/xMDtpdfFhQ0QrR1hmWFsHXd4zgvnEZvP3LQaa8vpojFbZWu15bEUlOKxg0IZXqEhv71pe0Svsbv/0KU0QkPc8b2yrtH1dZaGXf+hL6j09Bqfbv0mCz3Y3pWKGzIZdejb3Gwo6VP/n1Gq2p2uYmNEjVYO/W2MxoXr+2P5qzoBpwerQRSYIDpWLIyh/Ka12sLRqI21VEZeWqQIfjVx6PlfDwA1RUdGv1+R8bzFZ+rrQwKzUWbRsNUwGUlpZisVhITU1t1nlHKmxMmbuaLfnVvHfDAJ6enEWQWkmmQccVMWG8fKQEWyt9eAZQyGXcMSqNRXcMx+r0MOX11Ww+UtVq12sLIslpBVHJJtL6R/HbwlwcVnfjJzSDvbaGfWtW0fv8i1AoW29KleSTWPnfvZgidK2yJN5id2M6tnwxOCqarv0Hs/2n/yFJp2550B5V21ynDFWdzdKj6gqe7S8VQ1b+UF7rpNqTgcHQg4KCTwMdjl+VlC5GJnNxMDeOiorW65kA+L+DRfTQa9u8qN7evXtRqVTNSnJ2FJiZ8vpqfD6JhX8bzujuJ/c83ZMSTZXbw/sF5f4O9xS94oNZ+LfhdInUc81ba/lhZ3GrX7O1iCSnlYy4Ih2vy8tvXx3wa7u7Vi7D5/P9f3vnHR5Vmfbhe3ommUx6r0BCEkoI3VCVjgoqFhQRpNhWUXGta1n1s7Au6tp1FV1BQcUuovTeewskIQmk9zZJps/5/hgSKUlImWSScO7rygXMnPO+zxNmzvmd930Kfdp4FefkzjzyUsu5enIExuPFVPx5hrIfUin5+iRFnx+neGkSpd8lU/5bGlW7cjGmV2CraZqgs1htVJusbEkpYsn2DDaeKqDvuEkUZ54hN+VUm/rlKMr15iuixkRTcXdREOzhIgYfO4iSKiO+GhUhITMoLtmIXp/tbJMcgiAIZGd/hbfXKCwWD5KTk9tsrqO6GraXV/FYZCDSds4YSk5OJioqCoWiadeI5HwdM5fsIdTblR//Npxuvpc2eo5Qq7g90If/ZhVitrX9w6CXm5Jl84YyNs6fB5cfZHNy28aZthVidlUb4eapInFaFFuWJxM10J/wXo7pQ3Jiy3qihiTi6uHpkPEuxqozUb4vH/2fZ7jeS4Hk1zRKAZmHEqm7EqmLHIlKBhYblhIzthozll15cO5LpwjV4BLjjbqXD8qQ+suZy6QSpvUP4Uh2Of9ecwqD2cbyeUPw8A/gxJb1hMTEtYlvjqSsxiyu5FxEdIAYfOwoiqtM+GpUBAXeSHr625w58wFxca8726xWU1S8lqqqJAb0/5qePc9y+PBhEhMT22TbamlOCUEqBZNb0ezSZjOh0x2nqiqZquoU9PosLBYdVmsVgmBFJtMgl2tQqQLQuPXEza0nRmMIOTk5JCYmNmmOM8XVzFyyhyAPNUvnDMHDtWFhNCfUl6/ySlhbUsF1fp4t9qupuChkvHN7fx746gD3LTvA0rlDGNq9c/XUEkVOG9J7RDDph4tY93kSt/1jMO7erStgV1FYQNHZDIbe5Ngy6IIgYDpbSdWuPPTHixGsAkqpBM3VYbjFeKEIcEOqbvijIlhsWIr1mLKrMKSUUrUjB92GTBShGjRXBePazxfJeUUEJRIJb01PAMBgthL7/J/kVRqJGjKMU9s3I9hsSBzcDdjRlNeYCA4SC9+dT88ADWtOtE0c2pVGUZWRYA8XZDJXIiMe4HTaIiIi7sPVNdLZprUYQbCRnv4fvLyG4eV1FQMH+vLVV1+RlZVFeHi4Q+fSWaz8WFjG38L8kTczG8liqaKw8E+KSzZSWroDq7UKkOLq2g1XdQRqdShyuTsSZFisVVgsOqqqkikoWIXNZiAtbQhKZQ/UrtvR6z0bbUBaZbQw78t9uKvkLJvXuMAB6K1RM0jryrKcknYROQAKmZT3Zwxg7v/2ce+yA6xaMKJTZYuKIqcNkUgljJ/bi+9e28eaT49z02MDkDWQjdMU0g7sRSqTE9lvgMNsNGXrqFidgTG9ArmPC8X+buxPLWfK4wPxjmzaTVwil6IIdEMR6IbboAAEq2AXO7vyKPs+hYo1Z/CYEIHrwIBLage5KGRoXeQU6owMHTiUA6t+Ij8tlaBoxxQebCvKa8x1hQBF7EQHuPPZ9gz0JitqBweqX2mUVBnpG2JfgQgJmUFm5mekpS2mb9/3nWxZy8nL/5Hq6hTiYl8FoHv37nh5ebF//36Hi5zVRRXorTZmNKN1Q3V1GtnZy8jL/wmrtRoPbQIREffi4z0SN7eYyxYtFAQrlZXp7Nm9gojISrKyPuDMmcX4+o4hNOQuvL1HXLBiJQgCT35/hIJKI788NBxfTdPqhN0Z7MPCU1kUGM0EqNpny9xFIeOjOwdy/fvbeODrA3x//7BO06euYz8udwHUGiWT7u1LcVYV6z4/0aq08oxD+wjr3ReVa+tVtLXaTOk3pyh8/zDWajM+s3qR29ePHSfLSJzek4AmCpz6kMgkqON88Jvbh4DHB6Hq7kHZD6kUvHMQ45mKS47317pQqDMQHBOHi8ad9IN7W+NavVQZLVgcmJVQVmO6oBCgiL0goJhh5Rhqt6sAZDIXoqKeorDoD4qLNzrZspZhMpVw+vQiAgKm4OFhf0iTSqUMGTKE48eP11UHdhRriisYqHUl2OXyDyIGYz5JJ59i956JFBb9QVjYbIYP28agQd/TLfJBtNr4JlVllkhkHD9eiMUC105+lpEj9hAb8woGQy6Hj9zNgYPTqag4VHf8/3aeYfWxfBbfGk8Pv6Z1KgeY5OuBTAJrSy69lrYlHq4KPrpzIKkFVby8Kqld524NoshpBwIitUy8pzfpR4rZtOwUQguCxgSbjdyUU4TG9Wm1PYbkUgr+cwBDShme06IIeHgApwv17Po5nUHXRdJ7pONaECh81fjcEYv/gwlIVTKKPjlKxZozCOcJDn93FYU6I1KZjJDYXuSmOjYY0WoTGL5oI/1fXsfc/+3jv1vTOJpdjrWFwXsWqw2dwYKXKHIuoDbDSmzv0DpMFhsVejO+mr9u0AEBU/H2Hsmp5OexWDqfiExNfQ1BEOgZ/dwFrw8cOBBXV1e2bNnisLkMVhubSnVMvEwsjiBYOXPmY3btGktx8UZ69nyB4cO20aP7Y7i4NL+KvNFoZMeOHfTv3x8vLy9kMldCQm5nyODfSOj3P6zWGvYfuIXjJx4lvTCPN/5MZnZiBJP6NG8uL4WcIR5urCmubLaNraVPiAfPX9+L5Xsy2ZXWtplxjkIUOe1Et35+jLs7jlN78tnw5UmszawmWZqbg0lfQ1BUy7dxBJtAxR8ZFH9xAkWQhoBHB+A2OJAjm7LY+k0K/caEMeT65tV1aCrKMHf87uuHdnwEui3ZFH58FKvO3hrB311FUaURgKCoGPJPpyDYHLfqojOYqdCbGdnTF7PVxtvrUpn6/g4SXlrLvP/t49Ot6RzLrmiy6KnQ27PIPNTidtX5uKnkhHiqRZHTSkqr7d+L87cvJBIJsTGvYLFUkpz8QqcptQCQn/8r+QU/Ex39DEql7wXvKZVKRo4cydGjRyksdEz2zu6KKvQ2G+N9G16N1uuzOHDwDtLSFxMacifDEjcSFjoLqbTl3+ndu3djNBoZNerCPnwSiQQfn5EMGfwLcXH/orh4K48sW4nWxcYTk2JbNNdEHw+2lekwOvA62VRmDAlnSKQ3//jpWKco/inG5LQjPYcEIpFIWP9lElXlBibd2xcXt6atBuSnpYBEQmBUdIvmFsxWSr9LQX+8GI9ru6EZGYJgE9j2TQrHtuTQf0I4iTf1uGDPeMKECeTn5yOVSnF3d+fdd9+lf//+LZof7NtY2jHhuER7UbwsicIPDuM7pzf+Whf2nSkjOV+HxTsMk76G/UeTcQ8M4fxr+fl/l8skuCpluCnlqJWyuq679VErSmYOjWBYlC8mi41jOeXsTi9lV1oJb65LxmC24e4iZ0ikN4k9fLiquw9xQdp6S6iX1bV0EFdyLiYm0F0UOa2kuMou+C+O0VCrQ4mNeZUTSQvRevQnLPQuZ5jXLKqqUjh56h8EBtxAUODN9R4zcOBAdu/eze+//87s2bORtjLpYH9FDd4KGTGu9Sd6lJRs5djxBSgUngwc8A2enoNaNR/Ym3Fu27aNIUOG4OFR/wqSRCIjOOgW9ub15lhROg/3/4jCnFTcuj3c7OyyoZ4ajDaBEzo9AzwuTTdvS6RSCa9N68u172zjv1vTeXhsy+5J7YUoctqZ6MEBuHmqWP3xUb5ftJ9xc3sR2O3yKY6lOVloff1QuTb/A20zWin+4jjmnCp8Zsah7u1LVZmB9f87SW5qOVffGVPvFtV3331X10H3p59+4u677+bIkSPNnv9ilGHu+D+YQMkXJyj86Ai9B/vw33I9E/+zFbW1hvnAU0s2kO7W9FUlmfQv0eOqktX9XaOSYzm3QlNbfFAplzIwwpuBEd48eE0UJouNo9nl7E4vYVd6CYvX/iV6hnbz5qruF4qeCr39SdvLTVzJuZiYQHd+OZTjbDM6NUW1Isf90s9XYOBUKioPkZr6Khq3nnh5DW1v85qMyVTKseN/Q60OIzb2lQZv5HK5nClTprB06VIOHTrEwIEDWzXvwcpqEtxd650vJ2cFySn/xNt7FH16v41c7t6qucAeQLxq1Src3Ny4+uqrGz3WahN4f3Mho6J9uWnoJNLT30JvyCQu9vVmrSL11rigkko4qKtpd5EDEOWv4a7ECD7dms6sxIgOnYQhihwnEBztyS1PDWLd50n8+O+DDJocwcDJkcjkDT/BVBQW4OHX/N4rgtlGydITmPOq8b2nL8owd1L25bN1RQpypYypD/cjNLb+DIRagQNQUVHh0FoWcg8VfvfHU/zFCQbtK+G36QMw+7ggCAJbn13BI0O9iRg9vO742plrTTBbBfQmK9UmCzUmC9VGa92ferOVKqOF6nM/RouVkdG+9RbYArvoGRTpzaBIbx4aE43RYuVodgW700rYnVHCv9ckY7TY0LrIGdLNp64IoKdYDPASYgLcya0wUGkwo3URfz8toaTKLqK9GxDR0VHPUF2dypGj9zKg/zK02rbpFt4aLBYdh4/MwWyuYNDAlchkjSdLdO/enYSEBNauXVuXddUSBEHgsK6GOSG+l7x35szHpKX/m5CQmfSMfh6p1DG3v8TERDIyMvD29ubHH39sdMX71yM5nC6s4s1b+9EtbChqlzCSTj6FyVRCv/hPkEqblmGllErpo1FzsNJ5vaUeuLoHy/dk8um2dJ6Y2LJtt/ZAFDlOwtPflWlPDODA6jPs/+MsKXsLSLypB937+9UrJiqKCvAJaV6apWATKFl+EuNZHX5z+1Bug51vHSI3tZyoQf6MviPmsttls2bNYtOmTQCsXr26WfNfDqmLHN85vSn69Bg+v5/F//5+yH3VHAsIxN2sIyHM06HzNRWVXMbgSG8GR3qzALvoOZJVwe70Enanl7AttQg3paxDP704i54B9ifjlHwdgyKbnr4r8hfFVUa0LvIGe55JpUri+37CocOzOXR4DgMGfI27puPcZCyWKg4fmY9en8mA/subXNtn4sSJnDlzhu+++465c+c2uVrw+ZRZrJSarcS6XdhtPCt7KWnp/6Zb5AK6dXvEYQ9subm5jBkzhsTERKZMmdLoircgCLy38TTj4gLod+7aFhg4FaXSlyNH53H8+CP06fN+k8VXjJsLJ6r0DvGjJfhqVMweFskXO85w3+geHfahRgw8diIymZQhU7oz/dnBePir+fO/x/nhjQOk7Mu/JDC5qqwUd5/mVZqsXHcWw6lSuDqUjWsz+X7RfgzVZq5/qB8T5/dpUjzQ0qVLycrK4pVXXuGpp55q1vxNQeoix3duH6Quckq+SsJmsqLx9qGqtONE7qvkMoZ08+bhsdEsv+cqjr44ga1PXoOykZW3K5Ue/m7IpBKSxbicFlOsM162Zopc7kZCvyWoXUI4cGA6JR2kiafBmM+Bg7dTVXWKhH5LcHdvevVytVrN9OnTKSoqYvXq1S0Krs4y2FfBws5LHc/P/5WUlJcID5vnUIFTU1PDt99+S2RkJJMnTwYaX/HelV5CelE180deuA3v7T2Mvn0+pLhkE6dOPdNkv8NclHX+Oos5wyMxWmz83IG3qMWrdAfAJ0TDlAUJTH04AblSxrolSXz5zA62r0wl61QpVosNi8GAwkV9+cGwPzHkb81GtymLDJmUX75Po6yghmvuimX6c0OI6NP8styzZ89m06ZNbdJQT+amwOeuOCwlBsp/Oo1SpcZsMjp8HkehksvwaWLhrisNlVxGN183kvNFkdNSSqpNTSoMp1B4MGDAcjw9BnDkyDxyclY4NeuqUnec/ftvxmwuZ9DA7+rq4TSHoKAgrrvuOg4dOsTmzZubfX6m/kKRo9Od5OSppwkMvImoqGccJnCMRiNfffUVZrOZ2267jblz5xIWFsbzzz/PsmXL6j3n6z2Z9PBzY2i3S1c4fX2voVfcv8nL/5Hs7KVNsiHcRUmp2Uq1xXkZTgFaF8bF+fP17swOm/Enbld1IMJ6eRPWy5vSvGqOb80hdX8BRzZkoXCRYajRk3miAjfvHFw9VChdZChd5JhNVkx6C8ZqM6V5NZTmVlF+tpJEBEoF0PfQcuOsUIKjPZv1BS8vL6empobgYHsH8p9//hkfHx+8vdtmC0IR4IbXzdGUfpOMr0cQmYaTbTKPiOMp1Bm47eNd2ATQquUUVBpEkdMKiquM9QYd14dcriE+/lNSUl/mVPJzlJRuJy72FRSKlsW0tARBsHL27KekZ/wHjSaGfvH/RaVqfvxgLf3796eqqooNGzagUqkYNmxYk88tNJlRSiR4K2SYzZUcO/433FyjiI1pOPC5uZjNZpYvX05JSQl33303np6eLF1qFyZffvklTz311CVb++U1JtaeyOfpyXEN2hEYOJVK3VFST7+Gu7YPnh6NB2AHnqt2XGCy0L2Brc32YMbQCGZ/vpfDWeX0D2+/z11TEUVOB8Q7yI1R03sy8rZoirOqOHOsiK1LrZQVmNmyPJmGBLPGS4V3sIbBvi4oa8z0e2wgCm3LVhwqKiq49dZb0ev1SKVS/Pz8WLVqVZs00qvFNcEfQ3IZAfv1HMz+o83mEXEshzPLOVNSw7QBIagVMnr4acR4nFZQXGUi0qfpGTNSqZzYmJfx8krk1Knn2L3nWqKjniEg4HokkrZdrK/UHScl5WUqKg4SEX4v3bs/0uTg2cYYOXIkRqORtWvXYjKZGD16dJOuPTVWG64yezmJ5JR/YjaX0z/hS2Sy1vUNrBv/3BZVbm4ud911F0FBFxbymz17Nvfffz8lJSX4nBdesPFUIWarwJT4xgv/RfV4isrKY5w4/ihDh/6JXN7w58BVZhc2NVbn1qoZEeWLl6uCtUkFosgRaR4SiQS/cHd8wzRsWyZlyPXh9Ln6aox6Cya9BZPBglxpX9FRucpRqGTok0ooWZqE9x0xLRY4ABEREezd6/j2CpfD47pulB/MpL/P2HafW6RlpBdXo1HJefPWfm0qgq8UiqsuH5NTHwH+k/H0GMCp5Bc4kbSQzKzPierxJF5eju/yrddnkZ7xH/Lzf8bVtQcD+i/Hy2uIQ+cYO3YsCoWCTZs2UVZWxpQpU5DLG79l1Yqc4pLNFBT8Sq+4f6NWO6YvVmlpKV9//TU1NTXcddddhIeHN3nFe/3JAvqFeeKvbVxsSaUKevdazO49k0jPePuSCtHn43KuhleFE7erwF6+Y0xsAOuTCniqhcUN2xJR5HQCJBIJChcVZqMRmUKKq0KJq/bS5WzBaqN8VTouMV6o4/2cYGnrkWmU5HlmESHphfFsJaoIsdN3RyejqJpuvm6iwHEANptAabWpydtVF6NSBdAv/hPKyvZy+vTrHDp8FxpNLKEhMwkImNroysDlEAQrpaU7yM75iuLijSiVPsTE/B/BQbc5LB37fCQSCaNHj8bLy4tffvmFoqIipk2bhq/vpenhtRhsNlRSSE5+AW+v4QQG3uQQW44fP15XC2f+/Pl1qzRNWfE2WWxsSS7ib9dENWkutTqM7t0f5fTpNwgMmNpgiQDdOXGztqSS4V6tr/fTGsb3CuCHg9mcLakmohmrkO2BKHI6CXKlCrPR0Ogx1fsLsJYZ8J3Vq1PfcAolWfjJgqhcewa/ezpeDRCRC0kvrqK7X8e6sHVWyvVmrDYBH7fWbfl4eQ1h0KAfKC3dTnbO15xKfoGU1Jfx9ByKr8/VeHgOws01qtFtHEGwotdnUll5jJKSLZSUbsVsLkWjiSU25v8IDLzhsvVvHEF8fHxdDZpPPvmECRMmMHDgwHorI6ukUvRmHUZLEf0TlrX6OlhTU8Off/7J0aNH6dWrF9dffz2u5zVIbsqK98m8SqpNVob1aHrCR1joHPLzfyY19TUGDFhRrx9u5+JwBmud/91LPOfbvjNlosgRaRlqdy01FQ13nRUsNnQbs1DH+6EI7FgfsuZSo6ugyCsf1zQNhtPluER5OtskkUZIL6pmRFTnXDnsaNS2dPBr4UrO+UgkUnx8RuHjMwq9Poei4rWUFG8i9fQiBMEMSFGrw1Ep/ZDL3ZHJ3bBZDVisVZjN5dTUZGCz2R+sNJpYgoOn4+c7Fq02od0fokJDQ7n//vtZs2YNv//+O/v372fChAn06NHjguOUmKi2mAkJuR1X14gWz2c2m9m7dy9bt24F4KabbiI+Pr5Ffh/OKkcpk9IruOmr0lKpnB7dH+fI0fmUlm7Hx2fkJcdYzwVnhneAHnoeagU9/Nw4nFXGLQNDnW3OBYgip5Og9fOnsqigwfdrjhRhrTCiHeuY/WdnUllUiDTBBYVKg25rtihyOjAVNWZKqk3iSo6DKNbV37eqtajVIYSHzSE8bA5Waw1VVclUVadQXZ2K2VSKxaLDaCxEJlWhUHjjqo4kKHAabpqeaDSxqJQNbxG1F0qlkilTptRVRl62bBkREREMGTKE2NhYZDIZxsq9GAknMuKBFs1RVVXFwYMH2b9/PzqdjkGDBjF69Gg0Gk2L7T6cVU5csLbB4o4N4eNzNVptf9Iz3sbbe8QlAqvGaq+l5iq7cEXL0T0Hm0r/cC8OZ5W3+TzNRRQ5nQQP/wCyThxr8P3qPXmooj1R+Lf98nFbYjYYqKkoxyMgAE23IMp+SMVSakDu7ZjsCBHHkl5cBdBgywyR5lF8rgN5W9Zhkslc8fDoj4dH29/42oKwsDDmzp3LqVOn2LVrFytXrkSj0RAXF4PZuAOrR3fMMh+a+husqqoiNTWVlJQUUlJSkEgk9OnThxEjRjQa/9NUTuW3rHq7RCKhe7cFHD4yl4qKA5c0Ei0yWQDwVlx4G2+rnoOXo3ewll+P5GKzCUjraWzsLESR00nwDAji+Kb12KxWpLILnwhMuVWYMnX4zGx6ddGOSll+LgAeAUGou/lRviqd6r35eEyKdK5hIvViPdf8tL5u7SLNp1hnxEUhxU3pvLonnQGJREJcXBxxcXEUFBRw4MABkpIOYavy5G7paj5P3U94YAB+fn6o1WpUKhVyuRyTyYTBYKCqqorCwkIKCwvrCpyGhIQwduxYEhISLoi7aS3ZZTVM7RfconO9vUeiVoeTk7PiEpGTZTChkUnxumiFqC17DjZGmJcrJouNoiojAZfJImtPRJHTSQjoFoXFZKQ46yz+kd0veK/mYCFSjQKXuM5fmyQ/LQWJVIp/RDekShmu/f2pPliAdmJEpw6m7qpE+duX8U8XVhEXJGbCtZbiKiM+birxs94MAgICuPbaa/Hz/5IcnR8fZl/NDQobhYWFJCUlYTJd2PpAIpHg5uaGn58fUVFRjBo1iqioKNzcHL8aWVFjRmewEObdtGr1FyORSAkJvoP0jLeJNj2LUvnXNT7TYCLMRVnvZ6Utew42RJi3XRhmldaIIkek+QR0j0IilZJ/OuUCkSMIAvqTJah7+yCRdf4uHXmpKfiGRaBwsX9J1H18qd6VhzmnCmWoc9MkRS7F01WJr0bF6cIqZ5vSJSipMuHrLrYMaTI2G1RkYiw+guLMTkYF3sU6lxzCQ0OZEjYAPCOwufpgNBqxWCyoVCoUCkW7icjcCnsDzWDPlokcgKCgm0lLX0xh0Z+Ehsyoez2txkCkuv7PyuUqMLcFwZ72a3ZuReNZwO2NKHI6CQoXF3zDI8lNOUX8uEl1r1sKa7CWGHCZ0vx+VB2R3JSThMb2rvu3KtIDiVqOPqlEFDkdlCh/N1HkOIjiKiN+Gudny3RYLEY4sx1S10H2Xig8BeZqVEACwPEP+ADgxF+nSF19UQf0gsiRED0Bgvq1m7nVRnvcjNal5bdapdIHD49BFBevrxM5NkHgcGUND4U33j6joQrMbYGb0u5jrc8dBVHkdCIi+iaQtHUjgs2G5FyNCMOpMiQKKS49PJ1rnAOoKMynNCeLYbfeWfeaRCZBHeOFIbkMjwmRzjNOpEGi/d3Zk9FxusZ3ZoqrjMQGitt+l5BzAPYtgRM/g7katKHQbST0vgn840jKeQ+b0oU+Az5jUVo22/Jy+b23P5SmQ+FJyDsKO96FTa+CexD0nwkD54BHSJuaXWOyF+xTK1t3q/XzHcfptH9jsVQjl7txusaIzmpjgPbC2KH27jl4PlKpBLVCVudzR0EUOZ2IHoOGsv+3H8k7nUJwT3v5bGNmJcowdySKzr9VlbZ/DzK5nG4JF3YvVnbzoOZoETaTFakYkNnhiA7Q8M2+TCxWG/IusGXqTIqrWl7tuEtyej1ses0ucjzCYcSjEHsd+PeCc1tOVque/KwHiQ57FlTu9PYN4j8FRvK8YggK7Au9brCPZTFB5i5I+gV2fwTb3oK4KTDmOfCNbhPz60SOonXXLV/fMaSefpWy8t34+Y5lf0U1EqDfRSLHGT0Hz0dvtvLlzjPMG9GtXeZrCqLI6UQE94xF7a7l9P7ddSLHlKXDrb+/ky1zDKf37yGsdzxK9YVfXGWYO9jAnFOFqpuHk6zrGFgrKjCmpmJIScF89izWSh22Kh02kwmZmxtSjTsyH29UUVG49OyJMjISiULRpjZF+WkwWwXOltbQw6/l9USudARBaHHfqi5H/nFY+xykb4LwRLjjG/tWk/RSsVCpO44gWPD0sGcfjfDSIJPA+pJK7go+LwVcroTuo+0/41+CI9/YV3c+GAqD5sDV/wA3x27p1GoLoaGuyk1ErY5AofChsuIwfr5jWV9SyUCtK9qLMquc1XPwfHw72HarKHI6EVKpjJ5XDefk1o2MmH4XQpUFW6XJLgLaidpCUwBqtZoXXniBqKgoJBIJKpUKFxcXPDw8cHFpXnR9eUE+WUnHmHjfw5e8pwhwQ6KQYsrSXXEiRxAEDCeSqNq4kaotWzCcOBdsIJejDAtD5uGB1N0diUKBpbQM29lMLIWFWIqKAJC6ueE2bBiaq0ejGTMGuZfjuwSHeNmDKnPK9B1K5FQZLfxxLA+lXIq7ixw3pRyNixx3lQKNixw3lazZBdrakiqjBaPF1qY1cjo8Nitsfxs2vw5ekXD7coi59i+1UA+VlYeRStW4ufUEwEshZ6iHhj+LLhI556NyhyH3QP+7YO8nsPVNSPoVbngfek50mDuu51aea0xWWiOfJBIJHh4JVFYeQW+1salUx2ORjcfjOAOVXMqUFqbLtxWiyOlkxI+bzJF1f5B2cC9hXva6OPI2buNgs9nIzc0lNTWVm266ierqaqqqqjh58iTz5s3j/vvvv+QcDw8P/P39iYyMJDo6Gj8/v0aXTI9t+BOV2pWYYZeWL5fIJMj9XbEU6x3qV0fGptdTuXo1ZV8vx5CUhFSrRTNiOF4zZ+LSuxeqyEgkyoafmCxlZRhTU9EfOEDV5i3kPfc8EsXLaCdPxuvOGajjHdcTbG9GKRLJX+nkHYXVx/J48vujjR6jlEnrBI9GpcBdZf+7m0rOuLgAbuzftjEb51NSZU917mhPwu1GRTZ8P88eUDz8Ubj6Gfvqy2WorDyKu3vvC5qETvTV8lp6HjqLFffGhKzCBYY/AvG3wy8PwvLbYNA8mPQ6yOsXm82pKFwrcvTm1sepaLX9yMz8lK2llehtNib6dqwHPqtNwGix1fncURBFTifDP7I7QVExHFm7muAJ3UACcs+2efIrKSlh3759HDt2jOrqalxcXIiIiCAmJgZ/f3/Wrl3LiRMn+Pvf/44gCBiNRgwGA6WlpRQWFpKfn8+mTZtYt24dnp6eJCQkMHDgQNzdL1x5spjNHN+8nl6jxqBQ1b8CJPdUYSnrWKmJbYFgsVD+w48Uvfce1pISNKNGEfrxR2hGjEAib/rXVe7lhXzIENyGDMH3gQewlJRQ8dNPlK34hopffsFt+HD8n3wCl5iYVtv848EcErv7tCpNti0orzHhrpKz59mxVBksVBnP/Rgs6IwWqs/9W3fuverz3tuTUUp+haFdRU5d36orcSUn7wh8fRtI5XD3aohIbPKp+pqzuGv7XvDaFD9PXjqdy08FZcwKaULVYvcAuHMl7F8Cf/4Dik7B9K/A9dKA3eZUFNa62LeKK/TmJvvTEG6uUVgsOpbnFtDLzYVo1471Oak856O7S9tujzcXUeR0QvpPnsLq9xZT3iMXmbsSidyxwZ7Z2dls2rSJtLQ01Go1CQkJxMbGEhoaikwmu6TQ1MWiJSwsrO7vZrOZM2fOkJSUxI4dO9i6dSu9e/fm6quvrktpPLZxDfrKShImXtegTTJvF8xJXTuDp2bfPvJefAlTWhraqVPwe+ghlOGO6UUm9/HBZ/58vOfMQbd+A0VvvUXGjTfhcfM0Ap58Epm2ZRk92WU17Eov4c1bHZeWu3hNMvvOlKJWylAr7D8u5/1drZThUvd36bk/5ee9L8VFISO/wohWrcBVKcdVKac5kWvzv9yP1WZzmE9NoVbkXHHbVanr4btZ4NcT7vjWLjiagd6Qhb//tRe8FuyiZIKvli9zi7kr2KdpgbcSCQyeDwF9YMUdsGQCzPwBvC5s9NmcisK1wj+nTM/gyCa7VC9qdSgleLO+VM9rPUM7XMHInHL7SntIB3vYEUVOJyRm2Eh2//gtBSdSCAmMddi4ZWVlrF+/nhMnTuDn58eNN95I7969UVwUuNqcQlMKhYLo6Giio6OZMGEChw8fZteuXXzwwQcMHjyYYYlXseen74gbeTXewQ13r5VplVh1pgbf78zYTCaK332XkiWfo+7fn8jvv0fdp/flT2wBEpkM7cQJuI+5hrLvvqPoP+9QvWMnwa+/jttVQ5s93s+HclArZEzqE+gwG78/kI2nqwJPVwXVJislVSb0Zqv9x2TFUPt3s5XLxXPGh7ZsSV9nMLd71dbiKhMyqQRPdcd6Em5T0jfDNzOgxzVwy+egbN7Wu9lcicVSiYv60hW3u4J9ufNoOvsraxjs0Yxxw6+C+evhq2mwdCrM+RO0QRcc0tSKwm4qOd5uSrJKa5o+fwO4uISymXEoJTamBTg+tq61ZJfZfaytfNxREEVOJ0QqlTH8tjsp/ioJk0/r41QEQeDAgQOsWbMGlUrF1KlTSUhIQCptfIWouYWm1Go1iYmJDBo0iN27d7Nt2zYOHziAzCKQePMdjZ4rUcoQzDYEQehwTzCtwVxQQPYDf8OQmorfYwvxmTsXiazt97QlCgXed96J+zXXkPv0M2TOmYPvgw/i++DfmvX7/eN4Pp6uCnallXB1jF+rU8gFQaC0xsT9o7tz9/DG01AFwR4DYDhPANWcL4JMVnq0ME5IZ7AQHdC+l8fiKiPebsoO1dywTcnaCytm2Ovd3La0wRiYxjCZigFQKS9dp7va251oVxVvnclnRb8ezRvYpwfM/g0+nwTLbrRvoZ2XedWcB70wLzVnHSByanBjjeQ6pmpLGo8zchJnS2pwU8rwcu1YIl0satFJiR4yDDeNF8W5Z7CYW77fW1NTw4oVK1i1ahV9+/ZlwYIFDBgwoF6BU15eTm5ubt2/W1poSqFQMHLkSO6ecQe2yjJqQnuw48BBLJaGK2VKZBIQQDC37xZCW2I4dYozt03HUlZG5Dcr8L3nnnYROOejCA4m/H9f4PfwAorff5+8p59GMDV9xWzBmCh8NSrmL93PyDc28fa6FPIqWi68a0xWTBYbXm6XDziVSCS4KGR4uioJ8lDT3U9DnxAPBkV6MzLajwm9A1uc7aUzmts9tuCKSh8vz4Tl0+3Vh29b1iKBA2Cz2T9rMtmlWyQyiYTHuwWyqVTHvorq5g/uGQ6zfoWaEvh2Jlgvvc7Onj2bTZs21TX5rI9ewVqO51Q0f/6L+CS7CDMK7tJmtnqstuBoTgW9grUd7iFUFDmdFIlUim9oBAZ9FXt/XtmiMUpLS1myZAlZWVncfvvtTJ06FZWq4YtNRUUFN954I3379qVfv368//77LS40JQgCu7/5Eh9dMRPGj+fgwYMsW7aMmpr6n3iMZyoBsHaR4OOaAwc4e+dM5D4+RH7zDerebbM91RQkUim+DzxA8JuLqVz9B5n33YfN0LTf86Q+Qfy2YAS/PTSCq2P8+HRbOsMXbWT+l/vYeKqgrkt5UymrsQssL1fnZhjpDBbcW1GKvyWUVJmujMwqs8Eeg6PUwO1fg7Ll2xtWa63IqX+MKX6e9HJz4dW03JbVqvGNsgcgZ++F9S+26EEvIcyTlAJdq9odFJnM/DeriPHCn7iZT7d4nLbkcGY5/UI9nW3GJYjbVZ0YlZsr3sFh/PHzx/QYOISA7lFNPjc7O5vly5ejVqu55557mrQa48hCUyc2ryfj0H5ueOJ5ogYNJTQsjBUrVrBkyRJmzpyJ10X1XBQB9j11qVvHWgptCfrjJ8i6735cevcm7KMPkbZB9+OW4HHddcj9/Mi69z5yHnmU0PfebTRN/Xz6hnrwemg8/7g2jl+P5LJ8TyZz/7efYA8Xpg8O57bBoQR5XD4gsaza/rTs3YSVnLZCEIRzIqf9V3JCvTpWPEObsOYfUJAE89bUm73UHGw2e7C2VFr/w5lUIuGFqGBuP5LOd/llTA9qwXzhV8GEV+DPp6mQdePWf/y3WRWFE8K8sAlwJLucYT2akOlVD8+n5qCUSpjCT+Tm6YiLe71F47QVhToDOeV6EsI9nW3KJYgrOZ0YiVKGl28QvuGR/PrW6+irdE06Lzc3l2XLluHj48O8efPapa/J+RSeSWfDko/oc814ogbZg13Dw8OZP38+NpuNL7/8ksrKygvOkbrYt3GkHWy/t7kY09PJmj8fZY/uhH7YcQROLW5DhhD6/vtU79xJ7tNPIzQzw8jdRcGdQyNYtWAEvzw4nJHRfnyyNY3hizYy73/7WJdUgMXa8JiltSs5ThQ5NSYrVpvQqqaKLeGKWMnJ2GZP0574KgTXX1umOdSKm1qxUx9Xe2u5OcCLF0/nUGRq4db+0Psh9noiDi1i7+Y/OXbsGEeOHGH9+vUkJCQ0emqUvwYfNyXbUotbNPX6kkp+LiznpagQ3NERFHhzi8ZpS7al2H0bEtm+95KmIIqcToxEIQULTFn4DCZ9DX+8txibrfGiU4WFhSxbtgxfX19mzpyJq2v7Pjnqq3T8+tZreIeEMWbuhUUEfXx8mD17NjabjaVLl1Jd/dc+us1kBbkUSScOyrRWVZP94EPIfH0I/+QTZJqOJXBq0YwYXrd1VfLfT1s0hkQioV+YJ/+6JZ49/xjL/93Yh0KdkXuW7mfYoo18uy8TWz1bWWXVdpHj3U7bVUaLlQNny1h9LI/Pt2fw+uqTPPG9veaJtp1Xcoq6ekyOWQ+/PWJv0zBonkOGlMrsGXC121YN8VJUCBIJPJGc1bJtK4kErnvT3v9q3fPNOlUmlTAm1p91SQXNnrbYZOGJ5CxGe7lzS4AXCoUXrq4dpy9ULeuSCkgI88S/nTMSm4IocjoxUo0CW5UJD/8ArlvwOGeOHmLtJ+81+PRdXV3N119/jbu7O3feeWej8TdtgUlfw0+vv4ixpoapf38GhfLS+T09PZk9ezZ6vZ4VK1bUBSPbqszIXDvv7qogCOQ9+yyWwkJC33sP2Xm1Njoi2gkT8P3bAxS9+y7VO3e2aqza1Z3fFoxg1YIRWGwCT/1wjGGLNvLSbyfYf6a0TvCUVptwUUhRt1PV1NdXn+Lmj3byt68PsujPU/xxPJ9inYlpA0Lo345L7wazFZ3B0rVr5Ox4ByqyYMo7cJnMzaYik9of0qzWxrOXfJVy3o4N58/iSt7PLGzZZO6B9p5Xh76CzN3NOnVcrwBOF1aRUdz0AGirIPBA0hlMNoG3Y8OQSCRYrTX1Blk7E4PZytbUIsb36nhtJkCMyenUyL1csJQbEWwCkQkDmfS3hfzxwVso1WqumX3vBfvENpuNH3/8EbPZzNy5c9t9BcdsMvLzv1+hJCeL2154DQ//huuq+Pj4cPvtt/PFF1+wbt06Jk+ejLXMgMy74z0lNJXyb79Ft2YNIe++g6pbx3sSqw/fBx9Ef+QoOY8/QfffVzmk71WfEA/2PzuOA5ll/H40j9+P5vHFjjMEal2Y3DeQpNxKPNXtt2VTmwn2y4PDiQ/1cFpmSGl1F2/pUFMKO9+HIfeCX+urbNeiVNpjXEymosseO9HXg0ciAng9PY9+7q6M8m5Bz78Bs+3bbRv+D+5e1WhPrfMZFe2Hm1LGT4dyeGx8zyad83p6HjvKqvguoQfBLkrM5kpsNmOdzx2FtUkF1JisTOztuFpZjkRcyenEyLxcwCrUFcnrNfIaxs17gEN//Ma6/76H9byU7K1bt5Kens7NN9+Mh0f79jzR6yr54dUXyEtN5qan/9mkAOmwsDAmTZrEnj17OH78OJYyI3KvzilyzAUFFC5+E89bb0E7YYKzzWkyEpmM4H8tQrBaKVz0L4eNK5VKGBzpzYtTe7P7mbGsvD+RSX0C+f1oHnsySunu137beNMG2AtQhnqpnZr6WitynBlw3abseAcEG4xY6NBhFQotcrk7en12k45/slsgo73dmXM8g4OVLUgrl0rhmmfh7HbI2NLk09RKGTf2D+HbfZmNxqTV8klWIe9nFvJcj2BGeNnFmMGQBdiLAnYklu85y5Bu3h2ud10tosjpxMjPrWxYiv5aqu03/lomPvAoJ7Zs4Kd/vYSxpob8/Hy2bNnCqFGj6NGjmUWxWklZfi4rnn+c0pwsbn3+FUJjm54qPXjwYHr37s3vv/+Orqii067kFLzyChIXF/wff9zZpjQbua8vAU8+QcUvv1C1Y4fDx79Y8KxaMIJ3bm99QGpT0RnsDwLO7rdjtNhvfC6KjlfkrdXoy2Dvf+Gq+8HN8asQLi5hGAxNEzkyiYTP+kTSy03NjCPpJFW1oKZTz0kQMhA2N0/43zk0goJKI+tPNr5d9nVuCf88nctD4f48EOZX97r+nI9qdccROacLq9idXsqdQx3TfqYtEEVOJ0buq0aikmHKqrrg9T5Xj2PaMy+RfzqFZU8/wg/ffYefnx8jR17a4butEASBk9s28fUzCwEJM155k+Cecc0aQyKRMHnyZBAEdpqTUIZ2zCeFxqjetQvduvUEPvsPZO28guYoPKZNw3XIEApeex3B2vpuyg0hlUroE+KBn3v7xaXoDGZUcilKB/d/ay5Gi/33qnKyHW3CkW/shfSG3n/5Y1uAq2sk1TVpTT7eTSbjq/huhLkomXboNDvLqi5/0vlIJDBsAWTutKfCN5FewVoGRnjxyda0eoOfBUHg/bMF/D05i7tDfHm2e9AFq4s11WnIZBoUistXl28vPtmShq9G5dC2Lo6mWd+ojz76iPj4eLRaLVqtlsTERP7444+699PS0rjpppvw8/NDq9Vy2223UVDQeET55casZdeuXYwZMwY3Nze0Wi2jRo1Cr299S4POjEQqQRmqwZR1aep4RN8E7nz9bUwePhSVlBDhqkC4TOaVo6guL+P3d95g9ftv0n3AYGa8+iaegUGXP7EeNBoNV/caRposnxyhczXoFASBonfexaVvX9wnTXK2OS1GIpHg/8TjmNLSqGykfH1nxBn1cOqjdiVH1QHL9bcKQYD9n0Pc9aBpTovUpqN170tl5TFstqYX2/NQyPk+oQd93dVMP5LG9/mlzZs05jpw84MDXzTrtEfGRnMos5zNyRfGEJltAk+mZPNKeh4LIwJ4PTrkku3TisojaLXxHaaicEZxNT8eyuFvV/fo0J/bZomc0NBQFi1axIEDB9i/fz9jxozhhhtu4MSJE1RXVzNhwgQkEgkbN25kx44dmEwmpkyZgq2RWhuNjVnLrl27mDRpEhMmTGDv3r3s27ePhx566LK9la4ElOFaTJmVCPWk47p5+1Kt9SHYy4OUtav44tH7Sdq6sdm1T5qK2Whg94/fsuSRezl79BDXPfwE1y54HBe31q3A9BSC8Zd6smnHlpalfzqJ6m3b0B8+jN/DD3eYC1NLUffti2bMGIreex+hFW1EOhpVxvavbFwfpnMix9krSg4nczcUp8DAOW02hVabgM2mp7qmeZWAPRRyvo7vzs0BXjx0MpPHTmVSbWnig6BcCf3vsq9SmZtehX1ktC9DIr1ZvDa5LqMwrcbAlIOprMgr4e3YMJ66aAUH7A9MlZWH8dD2a/Jcbc1/1qfgp1ExowNvVUEzs6umTJlywb9fffVVPvroI3bv3k1OTg5nzpzh0KFDaLVawN68zMvLi40bNzJu3Lhmj9n7XKn7hQsX8vDDD/P000/XHRcT47gI/c6MKsoT3aYszLlVKEMvzBbYt28fer2e+fMXwPTpbFvxJX988BZ7fl5JwsTr6DVyDCoHZFnpSoo5uuFPjq7/E0NVFf0nXcfQabej1rQge+EiBEHAkFLGsMgB/Jy+kZSUlE7zf1/y2RLUCQm4jRjubFMcgt+Ch8i4aRq69evRTp7sbHMcgs5g7hAi56+VnC4mck6tAk0gRLbdVrlW2weJREZF+X7cNbHNOlcplfJ2bBiDPdx4/nQOO8qqeDM2rC7Yt1H63grb34Iz2yB6fJPmk0gkPDEphls/3sXXezIxhbnySloeQSoFv/aPZkAD3dINhixMpmK02oRmeNd27E4v4ZfDubw+rW+HjyNr8bfbarWycuVKqqurSUxMJC0tDYlEckHtFRcXF6RSKdu3b29Q5DQ2JtiL1+3Zs4c777yTYcOGkZaWRmxsLK+++iojRoxocCyj0YjR+FcVzIsr6HYVVJEeSNRy9EklF4gcs9nMjh076N+//7kWCV5Mfewf5KacZP+qn9j0v/+ybfmX9Bg4hG79BxHZbwCu2qbHjFQU5pN+aD/pB/dx9ugh5EoVvUaNYdB1N7Z4a6o+LIU1WEsM9JzSmwhrGlu2bGlzkVNtriatPI30inQqjBVUmavQm/WoFWo0Cg2eKk+6e3Snh2cPXBX1i0Rjejo1e/cSvHhxp1/FqcUlLg71wIGUfftdlxE5lU7oUVUfXXIlRxDg1O8QM9lhdXHqQyZzxcNjEMUlGwkNndns8yUSCXcG+zDMU8MjpzK55XAa4320PNcjmBi3RpId/OPAK9LuYxNFDsCgCC+G9wnghd9PYBgewF3d/flnVDBujTTnLSregESixMvrqmZ41jYYzFb+8eMxBkV4MX1QmLPNuSzN/nYfO3aMxMREDAYDGo2Gn376iV69euHn54ebmxtPPfUUr732GoIg8PTTT2O1WsnLy2vRmADp6ekAvPjiiyxevJiEhASWLl3K2LFjOX78ONHR0fWO+frrr/PSSy81171Oh0QmQR3rjf5ECdrxEXU31KSkJGpqahg2bNgFxwf3jGPqY3HoSos5vnEdp/fv5tSOLSCR4OEfgG9YJD6hYag17ihdXVEoVZgMeow1NdRUlFGclUlx1lmqy0qRymSExPZmzN33ETfyGoesCl2M/kQJEqUUdQ8vhkmGsWLFCnJycggJCXHYHEarkX35+9iavZWduTs5W3m27j1XuSsahQa1Qo3erEdn1qG3/BULFqmNZHjIcEaFjGJQ4CCUMnsKcPm33yLz8sJ9QtMvfp0Br9unk/vEkxjTM1B17xz1fhpDZ7DgruoIMTlWpBKQd+KK3pdQlAxlGRDzRptP5ec3ntOn38BiqUIub9n2eDdXFb/0j+KXwnJeS8/jmr2nGO+rZU6IL6O83JFe/LAikUDMtXD8R7j+7cvWzKmx2vipoIz/5RRzzE+KJlXKqFwL/5oUetkHoeKi9Xh7XdVi3xzJOxtSySqr4ZO7BiLtBJ/XZoucmJgYDh8+TEVFBd9//z2zZ89my5Yt9OrVi5UrV/LAAw/w7rvvIpVKueOOOxgwYMBlY2caG7M2nue+++5jzhz7vm7//v3ZsGEDn3/+Oa+/Xn+jsmeeeYbHHnus7t+VlZWEhXV81dkS1P38qDlUiDm7CmWYfTVn//79dO/eHR+f+iPx3b19SbzlDhJvuYOq0hLOHjtM0dkMirPOcnL7ZozVVZjOBXZLJFJUrq64uLvjExpBn6vHE9CtB+F9+6FybbuaJoJNoPpAAerevkgUUqKjo9FqtRw4cMAhIudMxRm+Tf6WX9J+QWfSEeQWxMiQkdzT9x6ivaLp5tENtfzS6qI15hoyKjJILU/lSNER1p9dz9cnv8ZD5cFNUTdxa9TNGH79DY8bb0TaxAaXnQX3CROQvvIqFb/+gv+jjzrbnFajM5gJaMdsroYwWWyo5LIus+oHwNkdIJFBZMMr7o7Cz3ccqamvUFKyhYCA61o8jkQi4cYALyb7efBdfilfZBdz+5F0wlyUTPDRMs5Hy1WeGtSyc/e0HmNg94d2Mefd/ZLxik0WtpRWsr6kkg2llegsNsb5aHlucDSG0GDuW3aAz7ZlcM+oS8+txWwuo7xiHz2j/9livxzFxlMFfLQ5jScnxRAd0PpwhPag2SJHqVQSFWUv5jZw4ED27dvHO++8wyeffMKECRNIS0ujuLgYuVyOp6cngYGBdO/e8H/g5cYMCrJvfdSu7NQSFxdHZmZmg2OqVKp2b1vgLFx6eiHzVFG1Jw/vMHcKCwvJysritttua9L5Gm8feo8ee8nrgs2GxWxCrlQ55eJrTCvHWmLA7VZ7hVCpVMrAgQPZvn07EydObPH/75mKM7xz8B3WZ67HU+XJLT1vYUr3KUR5RjXJT1eFK719e9Pbtzc3Rt2IIAiklKXwW9pv/JD6A7v//IKXy6zoRyS0yL6OjFSlwv3q0VRt3NRFRE7Hya7qUltVADkHIKA3KNu+urpaHYaHtj+5eStbJXJqUUml3BXsy8wgH/ZVVPN9QRl/FlewJKcYKdDdVUWMmwvRBPM0sOHoRpK7a9BZrFRYrGTojZyqNpBntAfpx7urmR/qx/RAbyLU565b3u7cN7o7i/48Rd9QD67qXv8DaV7ej4AUf3/nZmhmltTw6DeHGRfnz/2j2rfeWmto9Wa0zWa7IPYFwNfXXvBp48aNFBYWMnXq1BaPGRkZSXBwMMnJyRcck5KSYq+hIoJEKsFtcCC6zVnYru3GyZMnUSqV9OzZtPLhDY8rRaFyXgG+qt15yANcUUZo617r27cvmzZtIi0t7RLhezl0Jh3vHXqPlckr8XP14+VhL3Nt92tRyVonhiUSCTHeMcR4x/Bg/wfZ9/wCKjW7uDPtSaYrDvFQ/4dwU3TMZpwtQTNmLBW//IopOxtlaMcpTNYSOkzgsdnW9YKOs/dDZPsF3f/976fJyjqJRrMXDw8f3n33Xfr3b11hSYlEwhBPDUM8NQiCwKlqAwcrazhZredUlYHfTVJmqEPJPL2L/8iG4C6T4S6XEaFWMj3Qm1g3FxI9NQQ0sCX6xIQYjmSVc/9XB/j23kRiAi9cHREEgeyc5fj7T0KpdF59nOIqI3f/by9ebkrevC2hU2xT1dKsb/czzzzD5MmTCQ8PR6fTsXz5cjZv3syaNWsA+OKLL4iLi8PPz49du3bxyCOPsHDhwgsCRceOHctNN93EQw891KQxJRIJTzzxBP/85z/p168fCQkJfPnll5w6dYrvv//eUb+HTo/bELvI0W3PIflMMlFRUcjlzr94txRTXjWGEyV4TrtwdcXb2xt/f3+Sk5ObJXL25+/nH9v/QaWpkgUDFnBn3J2tFjf1oZarCTmWj3LCVB5I6M6nxz5lc9ZmXh/5Ogn+CQ6fzxm4DR+ORKGgassWvO+809nmtApdRwk8tlq71kqOxWhPHU/8W7tN+eOPf3L8xLUEB93C8eNx3H333Rw5csRh40skEuI0auI0F21hZw5mTnUBc0bGN3tMuUzKJzMHcfunu5m5ZA8r70sk0vevB6LSsh3o9WeIi60/LKM9qKgxc9eSvegMFlbel4iH2vkrn82hWd+qwsJCZs2aRUxMDGPHjmXfvn2sWbOG8ePtwZXJycnceOONxMXF8fLLL/Pss8+yePHiC8ao3c5q6pgAjz76KM888wwLFy6kX79+bNiwgXXr1rV7i4KOjMxdiVtiMAXb08nNzSU2tnmplB2NynVnkXm74Dbw0s62MTExpKSkNFp/qRabYOO9Q+8xd81cgjXB/Dj1R+b2mdsmAgfAWlmJ6XQa7kOGck/8Pfww5Qd81D7M/nM2Hx/5uFPV+WkImcYNVa849IcddwNxBlabQI3JirYjbFd1tZWcimxAAK/2C0738QkkNGQG2TnLKS7Jbr8tdq9IKDt72cMawsNVwbJ5Q3B3kTPj092kFNiLuwqCQEbGu7i798HTc7CDjG0ehToDd32+h7wKPV/NG3qBAOssNOsRZsmSJY2+v2jRIhYtWtToMWfOnGnWmLU8/fTTF9TJEbkU99GhHN19EOCycVAdGVOWDkNSCV639kQiu/TC36NHD7Zt20ZhYSGBgQ2XEzdajTy7/VnWnlnLgv4LmNtnLjJp29Z00B87BoA63l60K0wbxv8m/Y//Hv0vHxz+gMzKTF4a9hIKmfNvrK1BHd+Pqq1Nb1DYEak617dK0yFWcmwdumpssyk/d9P3bN9Ccf/8537Wrk1BJnuOtWu3t8+knhFQmW1vXdHC77WvRsXy+Vdx9xd7ufnDnXw0cyBx3klUVBygX78lTomJTC3QcfcX+zBbbXw9f+glW2mdhS706CAic1NQHmbDXXBB2UnLAglWG2U/pqIIcsM1of4y8MHBwUgkEnJychocp8pUxT1r72Fz1mbeuvot7om/p80FDoDh6FGkWi3KyIi61+RSOX9L+BtvjHqDP8/8yf3r76fGXNPIKM1jwoQJxMfHk5CQwMiRIzl06JDDxm4IdXw85rOZWMrK2nyutqLSYA8K7QjbVUZzFws8rsgGJODRvjFbX331Dbv3vMns2W48/vgj7TOpZ5i9w3plbquGCfRwYeX9ifSP8OLuL/by1h/r0GgH4uM92kGGNp1fDucw7aOduLvI+fnB4fQO7px990AUOV2OQkkFAUofyn5MrbfVg6Nx9A22ansO5vxqvG6ORiKr/+lFqVTi7+9Pdnb9nYf1Fj0PbXyI02WnWTJxCeMiLl+I0lEYMzJQRUUhqadswuRuk/lswmccLz7Ow5sexmg11jNC8/nuu+84evQohw8f5rHHHuPuu+92yLiNoeppr09lumhltjPRUTqQg71OTpfarjJUgtKtxSsbrSE8bA7XT+nOli1bLwiNaDNU5wSAqZmNPuvB3UXBktmDuLVfFcuPD+GNPfeQXdZ+PRorasw8vOIQj3xzmNE9/Vh5fyLBnpeW0ehMdKFvlYggCBQUFBCe0ANzThW6TVltPqcjb7CmvGoq1mWiGR5ySYuKiwkODiY/P/+S181WMws3LySpJIkPx31IP7/27fVizslF0UgNnwEBA3h/7PscLjzM41sex9KMpoIN4enpWff3ioqKdlnaVgQHA3Z/Oyu6DrSSY7J2sZUccw00UA28LSgvLyc31/5ZlMs1pKVNwN0dzOYdbT95bYq8yTGrsxZTHhMD/49/TU4hXydj3FtbWLwmue7z2haYLDa+2JHB1Ys3sSm5kHduT+C9O/p3iAeA1uL8b7eIw6iursZsNuPXPQh3hZrK9WdRhrvjEu3VZnM66gZrM1go/SoJha8a7YSIyx7v5eXFqVOnLnl98f7F7Mnbw4djP3RKNpM5JwfXIY0HCQ4OHMzbV7/Ngo0LePfguzw26LFGj28Ks2bNYtOmTQCsbodO4TJ3d6QeHpgb2TLs6Py1kuP8y6A98LgLxeSYa9qlPk4tFRUV3Hrrrej1eqRSKX5+fnz40S2kpL6Mp+cg1GrHVUi/BKvJ/mfmTghrXYCwzWYh6eQTyOVapg29l8lDXfh4Sxqfbktnxd5M5gyP5PYh4fhqHJM4UWW08NOhHJZsSyeztIZbB4bx2ISeBGidVzrE0Tj/2y3iMMrLywG78NDGBGLK0lH6zSn8H+yP3LvtPrStvcEKNoHS71KwVpsJWNAHqfLyF3tPT0/0ej1Go7GuKODq9NUsP7WcZ4c+S2JwYrPtaC2CIGApKkIRcGlG2MWMDB3JwoELWbx/MfF+8a3eUlu6dClgb4r71FNPtYvQUfj7YyksbPN52grduUJtHSG7ymS1oe1kqbkdiYiICPbu3XvBa2ZzOXv33cCx4w8ycMC3yNooo9KRpKUvpqJiP/37f41c7o67HJ6YGMvMqyJ4d0Mq7286zTsbUpncJ4hJfQIZEe3b7M+vwWxld3oJ65IK+OVwLnqzlfFxAXx810BiA7WXH6CTIYqcLkRFRQUAHh4eSKQSvG+PpfCDwxQvOYbf/f2QubdNi4HW3GAFQaD859MYTpbgM6sXcp+m7f/WriBVVFTg7+/P2cqzvLjrRa7vfj3TY6Y32wdHIJhMYLUibWIPr1m9ZnGk6AjP7XiOOJ84QjStf9qcPXs2999/PyUlJQ229HAUUldXbPr2ixdwNDUmKxLJZVsOtQtGsw2VpgttVylcHbZ902ITFJ707fM+Bw7eRkrKi8TGvtY2W7nn+tURPqzx4y5DQcHvZGZ+SnTUP/C6KGU8yEPN69PieXpSHCsPZLFyfza/HslFLpXQP9yTuCAtPQPcifRxw91FjruLHKlEQpXRQqXBTE6ZnuR8HckFOvafKUNvthLiqWbO8EhmDA0nyKNzx900hihyuhAGgwGwd38He7aV37w+FH5ylKLPjuF3bzwyt7Z7WmzuDVYQBCpWZ1C9Nx+vW3qijmv6TbnWR4PBgCAIvLTrJXxcfHj+qued1v/HVmO/qEvUTbtgSCQSXh72Mjf9ehP/t/v/+GjsR822vby8nJqaGoLPxcj8/PPP+Pj44O3t3TzjW4j1nLDujAzt5oMgwO9H85g2wLmVm41WGypFFxM5DswgbClabV9iY14h6eSTKJTeRPV4wvGT1Iq5VmzPlZRs5UTS3wkImEpY2NwGj/NwVTB/ZHfmj+xOVmkNm5ML2Z1Ryq60Er7ek4m1gWQTiQTCvV3pGeDOI+OiGRPrT7S/pmv1SmsAUeR0IcxmM3K5/IKGqHIfNX7z+1L0yRGKPjmK7929HbZ11ZobrGAVKP/lNNV78/Gc0h23QZff4jkf5bnGl2azmZ9P/8y+/H18Mv4TXNsx2PFihHMiU+rS9N+vRqnhuaHP8dDGh1idsZrrujev7059sQirVq1ql4uX3oHVZJ1BlL+GUT39+GLHGW7qH+LUC77RbEVZT02oTouLFkzVraod4yiCgm7GbKkkNfUVZDJXukU+6NgJjOeEvrJlHcLLyvZy9NgD+PiMolfcG03+HIZ5u3JXYiR3JUbazbBYKaw0UmkwozNYsNkE3F0UuLvI8deqcFVembf7K9PrLorZbEahuPSCovB3xe/+fhR/cYLCDw/jO7t3Xbfy1tDSG6zNYKFk+SmMp8vxuiUat0ENF/RriNo5Tp0+xZtlbzKl+xSGBbduubi1SM797gVz87IgRoeNZmLkRN7Y9wbXhF3TLKFWXyxCeyFxdW3y1lxHZc6wSOb8bx8HM8sZGNF2AfqXw2SxoVJ0ocBjj1BAsNfL8W6/qscNER42B6ulivT0tzCby4iOegaJxEG/7/IskEhBG9zsUwsK/yAp6e94eAygT+/3kEpbLghVchlh3p37+9gWiCKnCyEIQoMCQ+Hniv/f+lGyNInCj4/gMTESzYgQJK1otNaSG6zxbCWl3yZjqzbjO7c3LlGtu7EcLziOQWrg0YGPtmocRyA9t01lq2l+nMrCgQu5/qfrWXFqBfP6znO0aW2CS2wsyrAwZ5vRKkb39CPSx5X/7TzjVJFjtHSxtg6e5zIkyzM7hMgB6NZtAXKFJykpL6PXZ9G711vI5Q5oU1B+FrShzVqxEgSBzMxPOZ32LwL8rycu7o1OERjdGelC3yoRpVKJyWRq8H2ZRonfvfFohgVT8UcGxZ8dw1zcPoGjNpOVijVnKPr4CDKNgoAF/VslcGp7QG0zbmN6zHT8Xeuvjtye1Mbi2PTNj0UI0YRwc/TNfHHiC6ocUFSsPbDp9UhcO3fAolQqYcbQcP44lofZevleaG2F0WLrWttVHqGABMoynG3JBYSF3kW/+E8oK9vJ3n3XU1FxsPWDlp0Br8uXvajFaCziyNH5nE77FxERD9C799uiwGlDutC3SkShUGCxWBptXCmRS/G8rju+8/tiKTVQ8NYByn9Nw1rdNoWmBJtA9b588hfvR7c1G+24CPzu64fct3U3R/O5LSGzxMzcPg0H6rUnEqkUmYcH1pLSFp1/T997qDHXsDJlpYMtaxuspaXIzquT1FmJ8tdgsQmUVjf8gNDWmCzWrhV4LFeBb0/I63hxW76+Yxgy+FcUCm/2H5jO6bTFWCyteLDIOwIBvS97mCDYyM//hT17r6Wy8hj94j8jqsfjSCRd6P+9AyJuV3UhauvFmEymuuyjhnDp4Ung3wei25GLblMW1fvzce3vjyYxGEVg65dwbTVmqg8UUL07D0uJAXW8Lx4TI5ucIn45qvXVACSGJeKjbttU6eagCA1tcYG8ALcAJkZOZGXKSmb3no20A1/8bCYTlsJClKHOzUpyBH4a+3elsNLotCJoXW4lByB0EGTvd7YV9eLq2o2BA77l7NmPOHP2Q/LyVtK926MEBd2KVNqM22JNKZSmQ8igRg8rK9tD6unX0emO4ec3idiYl1EqO851qysjipwuhIeHvYdKeXl5o925a5EoZGivDsNtUABVu/Ko3ptH9Z58FGHuqGO9cYnxQhGsaXLcjrXSiOFUGfrkUowpZQg2AXVfX7xvj3VIoPP57M2wxwLd0PcGh47bWhQhIZhz6u+p1RRui7mNVemr2J232+mB1I1hyc0FQWi0hUVnwV9rfzgoqjIA7d+IUBAEe0xOVwo8BggZCEe+sadYt2P146Yilcrp1m0BgYHTSE9/i1PJz5Fx5n1Cgm8nOHg6KlUTtsBrRVzowEvesloNFBSuIif7ayp1R9G6xzNgwDeX1MARaVtEkdOFqC2Q11SRU4tMo8RjfATaa8LQJ5WgP1aMbms2levOIlFKkQe4oQhwReauROoiQ6KSIZgFBKMFW40Fc1EN5vxqbDozSEAZrsV9bDhuAwParADh/oz9qGQq+gf3b5PxW4oyPIyK31tebTjBL4Eozyh+Tv25Q4sc47nGnJ098BjA202JRGJfyXEGZqs9vqxLBR4DRAwHwQpntkPPCc62pkHU6hB6936T8Ih7yM5eypmzn5Bx5j08PAbi63M13j6jcXPtUX/mU/om0ASCVzcEQcBgyKWsbBclJZspKd2G1VqFj/co4uP/i6/PNeLWlBMQRU4XQqPRIJfLKSsra9H5ErkU13g/XOP9EKw2jGcqMedUYc6vxpxfjfF0OTaDFcFoQaKQIlHJkaplyH1dcRsciCLQDVUPzzYtOAhgsBgoLi2mh3uPNp2nJbj06UPJZ0uwFBUh9/Nr9vkSiYQJkRNYemIpZqsZhZNrjDSE4egxZF5eyIObnzbb0VDIpHi7KinSOUfkGC1WgK7VoBPALwa8ukHy6g4tcmpx18QSF/saUT2epqBwFSXFm0jPeJfTaW8gkShwc+2O2rUbCrkWmVyDBCkRx76iKiCQ9IO3UVWVgtVaBUjQavsRHj6fwIApuLpGOtu1KxpR5HQhJBIJ/v7+5OXltX4smRSXHp649PBsvWEOZnfebjQGDeE9wp1tyiWo4+MB0B87hvuYMS0aY0zYGD48/CH7CvZ12NUc/dGjqOPju0zFVD93FYVOEjkmiz1RoEs16AR7md3Y6+DY93DdWyDtHCJOodASGjKD0JAZWK0GKiuPUFWdQnVVMnpDNkZjPhaLDnWlDmV1JaV+sahdwvD1GYtGE4NW2xel0tfZboicQxQ5XYyQkBDS09OdbUabsvnsZjzNnsR0i3G2KZcgDwpC5ueL/tChFoucnl49CXYLZkvWlg4pcgSrFf3Ro3jfPdvZpjiMAK0LeRUGp8xtPCdyutxKDkDs9bDrfTizDbqPdrY1zUYmc8HLayheXkMvfXP9S6DKJmrcb6DoOl27uxpd8Ft1ZRMaGkpJSQk1Nc7vG9NWpGamIhWkhHbAzB6JRIJm2HCqNm9p1RiDAgdxuOiw4wxzIPpDh7BVVqIZPtzZpjiMYE81eRXOaTb610pOF7wch19lTyU/8IWzLXEsFhMcWgb9bhcFTgenC36rrmzCw+1bOBkZHasIl6OoMlVhLjQjVUgJCGhev6v2QjNmDMbUVExZWS0eI943npTSFAwW56wuNIZu4yZkfr649O3rbFMcRoinC9llegor2//3bezKIkcigUFz4eRvUFXobGscx6lVUF0EA+c42xKRy9AFv1VXNl5eXvj7+5OcnOxsU9qEEyUnCKoJIqxbGDJZ+8QwTJgwgfj4eBISEhg5ciSHDh1q9HjNiOFIFAp0Gza0eM6+fn2xCBZOlZ5q8RhtgSAI6Dasx/3qa5B0khiLptA72IMKvZkhr21g9L83seiPU2SWtM9qaJcNPK6l3+0gU8Kej51tiWMQBPsWXPgwCOjlbGtELkMX/VZd2cTExJCSkoLVanW2KQ7nVO4pvExe9O/dfqnj3333HUePHuXw4cM89thj3H333Y0eL3VzQ3P11VT88GNd+4nmEu0ZjVQiJa08rUXntxX6Awcwn81Ee+1kZ5viUK6J9WfvP8bywYwBjIjyZcXeTK55czNPfn+ErNK2FTtdNvC4FrUXDLkXdn8M1cXOtqb1pPwJOQfg6qecbYlIExBFThckLi4Og8FAWlrHukE6gpzUHGwSGzE92y/o2PO81gUVFRVNyijyvH06xtRU9JdZ9WkIhUyBv6s/OVUtq57cVpR98y3KiAhch9YTiNnJ8de6cF18EK/e1Jc9/xjLP66NY+OpIq5ZvJnXVp+kxmRpk3m79HZVLcMfsXfq3v62sy1pHTYbbHoVIkZAt84XSH0l0oW/VVcuQUFBBAYGsn9/xyyp3lJsNhv6s3oMPgbU6vZtDDlr1izCwsJ4/vnnWbZs2WWPd0tMRBEeTtnyFS2eM9gtuEOJHEtJCbo1a/CcPr1LbVXVh4tCxrwR3dj25DUsHN+TL3eeYcLbW9mc7Pi4ki4deFyLqzcMewj2/heKOvFW+sEvIf8YjH3eHm8k0uHpwt+qKxeJRMKgQYNITU2loqLC2eY4jDNnziDTy1B3a//O10uXLiUrK4tXXnmFp566/DK1RCrFe+ZMKlevxtjCIPBAt0AKagpadG5bUPLZEiRKJR433ehsU9oNtVLGg9dEsXbhKCJ93Lj7i308vOKQQwsH1sbkdNntqlqGPwoeYfDrw/YVkc6GLh/W/RP6z7RnjYl0CkSR00Xp27cvSqWS3bt3O9sUh7Fz5070LnrUrexg3hpmz57Npk2bKCkpueyxntNvQ+7nR/EHH7ZoLjeFGzXmjlEKwFxYSNny5XjPno3cy8vZ5rQ7ET5uLJs3hLdu68e21CLGvbWF7/ZltTjm6ny6dJ2c81G4wJR3IGs37F/ibGuahyDA738HuRLG/5+zrRFpBl38W3XlolKpuOqqq9i3bx+VlZXONqfVZGZmcvr0aTL9MnFVtF+zv/LycnJzc+v+/fPPP+Pj44O3t/dlz5WqVPjefx+Vv/+OoQXZbmq5Gr3FObVbLqbk44+RqFRdqgBgc5FIJEwbEMqGv1/N2Dh/nvzhKHd8upv0oqpWjXvFiByAbiNh8HxY8yzktixezSns+dieNn7dW/atN5FOwxXwrbpySUxMRC6Xs23bNmeb0mo2bdqEv78/Oa45qOXtt5JTUVHBjTfeSN++fenXrx/vv/8+q1atanI7A8+bb0bZvTv5L/wToZnZbj+k/sCZyjMtsNqx6I8epWzFN/g+8AAyrdbZ5jgdbzclb92WwFfzhpJbbmDSO9t4b0NqXWxNczFabMilEmTSKyTGY+JrENAbvp0FNaXOtubyZO6Gtc9B4kPQa6qzrRFpJqLI6cK4uLgwYsQIDhw4QH5+vrPNaTFJSUlkZGQwZswYZDIZVqH9UuMjIiLYu3cvx44d48iRI6xfv56EhIQmny9RKgl6+SX0R45QtuKbZs0d7RndTGsdj2A2k/fc87j06oX3XTOdbU6HYkS0L2seHcW8Ed34z4ZUrnt3G/vPNP+mbbLYunbQ8cXIVXDbUjBVwTczwNQxtmTrpTgVvp0JYUNh3EvOtkakBVxB36wrk6uuugofHx9+++03bJ0w2E+v17N69Wp69uxJTExMh9rCaSquAwfieft0it56C2N604OQe/v2Jsozqg0tuzxFH36IMS2NoP97GYlcbHV3MWqljKcmxbJqwQhcVXJu+XgXz/50jAq9ucljGC1WVIouHnR8MZ5hMONbyDtqFxEW5zRHbZSys7D0BnD1gduWgUz8/HdGRJHTxZHL5UyZMoWcnBz27NnjbHOazbp16zCZTFx33XVIJJJOKXIA/B9/AnlgIDmPPIytiX3F9BZ9u27NXYxu82ZKPvoYvwULcOklVnZtjLggLT8+MIyXpvbm50M5jH9rC38cy2tSYLLJYkMpuwIvxWFD4I4VcGY7fHsXmKqdbdFflKTB0qn2Ss2zfgE3H2dbJNJCrsBv1pVHeHg4Q4cOZd26dWRnZzvbnCZz9OhRDh48yIQJE/Dw8ABAq9RSbix3rmEtQKZxI/S9dzHl5JL33PNNuvlVGCtwV7q3g3WXYsrMJPfJp9CMGYPPvfc4xYbOhkwqYfawSNY9Npr4UE8e+Pog9yzdT25546LcaLGhUlyhl+Luo+GO5Xah88W1oOsAJRMyd8Nn40CqgNm/gnugsy0SaQVX6DfrymP8+PEEBwfz3XffUV3dgZ6YGqCgoIDffvuN+Ph4Bg4cWPd6sCaY3KrcRs7suKh69CD4tVepXL2awkWLLit0cqtyCdYEt5N1f2EuKCBz7jzk3t4EL3q9yxf+czTBnmo+nTWQj2cO4Gh2BePf2sIXOzKw2ur//zaar9CVnFqixsHcP6CqAD4dA2d3OscOQYB9n8GXU8G/F8xbC57hzrFFxGFcwd+sKwu5XM6tt96KxWLhm2++wWQyOdukBqmsrGTFihV4eXlx/fXXX5DJFKIJ6VBVgJuLdtIkAv/5AqVfLqX4vfcaPTa7KpsQTUg7WWbHUlpK5py5CDYr4Z8vEbOpWohEImFSnyDW/3000waE8vKqJKZ9uIOk3EvLOZis1it3JaeWoH4wfz14hNpXdNa/CJZ2vEbpCuDrW+21cPrPhLt+FFPFuwhX+DfrysLDw4MZM2ZQUFDAN998g8XSNr14WkN1dTVLly7FZrMxY8YMlErlBe+HaEIo1hd3mCJ5LcHrjjvwf/zvFH/4EQWvv15vanmFsQKdSUeoJrTd7DJlZnJ2xp1YKyuJ+PxzFMHtv4rU1dC6KPi/G/vw/f2J6M1Wpry/ndf/OIne9Nf/udFs6/rVjpuCRyjMWW1vmbDzPfgoEU7+Zl9haSvMens/rfcHQd4RmLESrn/LngEm0iUQRc4VRmhoKHfccQeZmZl8++23HWpFR6fTsXTpUvR6PbNmzbqgMWYtcT5xAJwoOdHO1jkWn/nzCXjheUqXfUX2w49cEox8vPg48Je/bU3NoUOcmX47AJHLv0YZGdku814pDIzwZtWCkSwcF80XO84w4T9b2JpSBIDebL2yt6vORyqDkX+H+7bat4q+nQmfT4JTv4PNgaUjDJWw91N4fzBsfAXip8PfdkPPCY6bQ6RDIH6zrkC6devG7bffztmzZ/niiy/Q6XTONomCggI+/fRTampqmDVrFr6+vvUe18OjB65yV44VH2tnCx2P94wZhH7wPtW7dpFxy63oj/8l3I4WH8VD5UG4e9vGBAhWK8X//ZSzs2aj7N6diBXLUYaLcQhtgVIu5aEx0fz5yEhCPV2Z9fleHlx+kPUnC+gX5uls8zoWAb3hrp9g5o9gs9jr6bzTD7a8YW+Q2ZLVHYsJ0jfDqoXwVhz88RSEDoK/7YHrFosZVF0UieCI5iudgMrKSjw8PKioqEArxhkAkJeXx/Lly5FKpdx8882EO+nmduLECX799Vc8PT2ZMWNGXSZVQ8xdMxetUst/rvlP+xjYxhjT0sh94kkMKSn4/u0BfObN48FtjyIg8PG4j9tu3vQM8l54Hv2Bg/jMn4ffggVILtoeFGkbBEHg+wPZvLr6JG5KOWsXjsJNJdZhaZDcQ7D3M0j62V5EUBsCkSMhoJc9SNgjFFRacNHaRZGhEgwVUJoGhSftwihjG5h04B5sj7sZeDd4tG/Mm0jLaM39WxQ5VzgVFRV8//33ZGdnM2LECEaPHo28nYq+GQwGVq9ezdGjR+nVqxc33HADKtXl98I/PvIxX574kq3Tt6KQKdrB0rZHMJko+uBDSj77DFmAP+8PLiXhzgXMjZ/n8LksJSUUvf8+5d+tRBEYSPCi13EdPNjh84hcnooaM2abDV+NGAPSJCxGe/ZV6lrI2gtFp+yipzHc/ME/zt43K3oiBPaFJrZlEekYiCKnCYgip2FsNhvbt29n8+bNeHt7M378eHr27Nnk/kwtme/QoUNs2rQJk8nEtddeS79+/Zo8X3JpMrf8dgufjP+EYcHD2sRGZ2FMzyDp1Wdw2XEESWQY/jNn43HjDcg0mlaPbUhOpuzr5VT89hsSuRzf++/Da+ZMpE0QliIiHRKbDSqyQJcPxkr7j1QOKndQeYBXBLjVv/Ut0nkQRU4TEEXO5cnLy2Pt2rVkZGQQERHBiBEj6NGjB1IH1UmxWCycPHmSbdu2UVhYSJ8+fRg3bly9AcaNIQgCk36YxKjQUTx71bMOsa0j8c+d/6Rk7w6ezuiDbv16JCoVmlGj0IwejWbUSOQ+TYsdEGw2DEknqdqymarNWzAcO4bc3x/P6bfhNWMGci+vNvZEREREpPWIIqcJiCKnaQiCQGpqKhs3biQ/Px8vLy8GDhxITEwMvr6+zV7dsdls5OXlcfLkSQ4dOkR1dTXdu3dn7NixhIS0fD988b7F/JL2C+tvXY9K1nVWImrMNYxdOZY7Yu/g4QEPYy4ooOLHH9Ft2ozhmD3gUh4YiCo6GlX3bki1WmTu7kiUKmzVVVh1OixFRRhTT2M8fRqhpgapRoPbiBFoJ03CfewYJIquscUnIiJyZSCKnCYgipzmIQgC2dnZ7N27l6SkJKxWK15eXnTr1o2AgAD8/f3x9PTExcWlrpaNwWDAaDRSWlpKYWEh+fn5pKWlUV1djUqlol+/fgwePBg/P79W25dRkcHUn6eyaOQirut+XavH6yj8mPojL+58kT9u/uOSQoCWkhKqd+3GmJKCMTUV05kzWKt02HRVCEYjUo0GqbsGuZe3XQRFR+PStw+u/fuLwkZERKTTIoqcJiCKnJZjMpnIyMggNTWVrKwsioqKLtvRXKFQ4OfnR2RkJNHR0YSHhyOTObbg2fw18zHbzHw5+UuHjussBEHgjt/vwNvFmw/Hfdjsc9sqhkpERETEmbTm/i3mLIpcFqVSSUxMDDExMQBYrVZKSkrQ6XQYjUYMBgMSiQQXFxdUKhWenp54eno6LJanIe6IvYNHNz/KwYKDDAgY0KZztQe783ZzouQEH4z9oNnnigJHRERE5FLElRyRTotNsHHbb7fhrnTn84mfd+obvSAIzFw9E4Cvrv2qU/siIiIi4khac/8WKx6LdFqkEikP9X+I/QX72ZW3y9nmtIot2Vs4WnyUh/o/JAocEREREQchihyRTs3o0NEM8B/A63tex2g1OtucFqG36Fm0dxFDg4ZyVdBVzjZHREREpMsgihyRTo1EIuGFxBfIrsrm06OfOtucFvHR4Y8oqini+aueF1dxRERERByIKHJEOj09PHswv+98lhxfQlJJkrPNaRZHi46yNGkpDyQ8QIQ2wtnmiIiIiHQpRJEj0iW4p+899PTqyWObH6PCWOFsc5pEqaGUxzY/Rm/f3szuPdvZ5oiIiIh0OUSRI9IlUMqUvHX1W+hMOp7Z9gw2ofE6Ps7GYrPw1NanMNvMvDn6TRRSsVifiIiIiKMRRY5IlyFEE8KikYvYkbuDV3a/QketjmATbLy480X25e/jjVFvEOgW6GyTRERERLokosgR6VKMDB3Ji4kvsjJlJW8deKvDCR1BEPjX3n/xa9qvvDriVYYGDXW2SSIiIiJdFrHisUiX46bom6ix1LBo7yIsNguPD3ocmdSxLSVagsVmYdHeRXyb/C0vJL7QpXpuiYiIiHRERJEj0iW5M+5O5BI5r+19jZyqHBaNXISrwtVp9lSbq3liyxPszN3JS8NeYlr0NKfZIiIiInKlIG5XiXRZpsdO570x77E7bzcz/5hJSlmKU+xIKklixu8zOFR4iA/HfSgKHBEREZF2QhQ5Il2aUaGj+OrarwC4fdXtfHniSyw2S7vMbbaZ+ezYZ9y5+k6UMiVfX/s1w4KHtcvcIiIiIiLNFDkfffQR8fHxaLVatFotiYmJ/PHHH3Xvp6WlcdNNN+Hn54dWq+W2226joKCgVWOejyAITJ48GYlEws8//9wc00WuYHp69WTFdSu4I/YOFu9fzM2/3syWrC1tFpQsCAIbMjcw7ZdpvHvwXWb3ms3ya5fT3bN7m8wnIiIiIlI/zRI5oaGhLFq0iAMHDrB//37GjBnDDTfcwIkTJ6iurmbChAlIJBI2btzIjh07MJlMTJkyBZut4ZoljY15Mf/5z3/EsvciLUIlU/HE4Cf45vpv8FX78tDGh5j952z+zPgTs83skDlMVhO/p//OzNUzeXTTowS5BbFyykoeHfgoCplYB0dERESkvZEIrXyc9fb25t///jdhYWFMnjyZsrKyulboFRUVeHl5sXbtWsaNG9fsMefNm1f32uHDh7n++uvZv38/QUFB/PTTT9x4441NHrM1rdpFuhaCILAtZxufH/+cAwUH8FX7MrnbZEaFjmKg/8BmCRKT1cT+/P1szdnKHxl/UGooZWjgUOb0mcPwkOFt6IWIiIjIlUFr7t8tzq6yWq2sXLmS6upqEhMTSUtLQyKRoFKp6o5xcXFBKpWyffv2Jomci8espaamhhkzZvDBBx8QGCgWThNpHRKJhFGhoxgVOoqUshS+S/6ONRlrWJa0DFe5K7HesUR7RRPlGYWXixcahQa1XI3eokdn1lFmKCOtPI3UslROlp5Eb9ET4BrA5G6Tua3nbeK2lIiIiEgHodki59ixYyQmJmIwGNBoNPz000/06tULPz8/3NzceOqpp3jttdcQBIGnn34aq9VKXl5ei8asZeHChQwbNowbbrihyXYajUaMRmPdvysrK5vrqsgVQE+vnjx31XM8O/RZksuS2Z6zneTSZA4UHOCHlB+wCJcGKcslciI9Ion2jGZ02GhGhIwg2jNa3EoVERER6WA0W+TExMRw+PBhKioq+P7775k9ezZbtmyhV69erFy5kgceeIB3330XqVTKHXfcwYABA5BKGw/9aWzMX3/9lY0bN3Lo0KFm2fn666/z0ksvNdc9kSsUiURCrHcssd6xda/ZBBvV5mqqTFXoLXrUcjUapQY3hRtSiZiYKCIiItLRaXVMzrhx4+jRoweffPJJ3WvFxcXI5XI8PT0JDAzk73//O0888USLxnz00UfrRFMtVqsVqVTKyJEj2bx5c71j1LeSExYWJsbkiIiIiIiIdCKcEpNTi81mu0BMAPj6+gKwceNGCgsLmTp1aovHfPrpp5k/f/4F7/ft25e3336bKVOmNDiGSqW6ID5IRERERERE5MqiWSLnmWeeYfLkyYSHh6PT6Vi+fDmbN29mzZo1AHzxxRfExcXh5+fHrl27eOSRR1i4cCExMTF1Y4wdO5abbrqJhx56qEljBgYG1htsHB4eTrdu3VrsuIiIiIiIiEjXplkip7CwkFmzZpGXl4eHhwfx8fGsWbOG8ePHA5CcnMwzzzxDaWkpkZGRPPvssyxcuPCCMdLS0iguLm7ymCIiIiIiIiIiLaHVMTmdBbFOjoiIiIiISOejNfdvMUVEREREREREpEsiihwRERERERGRLokockRERERERES6JKLIEREREREREemSiCJHREREREREpEsiihwRERERERGRLokockRERERERES6JKLIEREREREREemSiCJHREREREREpEvS6gadnYXaws6VlZVOtkRERERERESkqdTet1vSoOGKETk6nQ6AsLAwJ1siIiIiIiIi0lx0Oh0eHh7NOueK6V1ls9nIzc3F3d0diUTibHPalMrKSsLCwsjKyuryfbpEX7suV5K/V5KvcGX5eyX5Cm3jryAI6HQ6goODkUqbF2VzxazkSKVSQkNDnW1Gu6LVaq+ILxWIvnZlriR/ryRf4cry90ryFRzvb3NXcGoRA49FREREREREuiSiyBERERERERHpkogipwuiUqn45z//iUqlcrYpbY7oa9flSvL3SvIVrix/ryRfoeP5e8UEHouIiIiIiIhcWYgrOSIiIiIiIiJdElHkiIiIiIiIiHRJRJEjIiIiIiIi0iURRY6IiIiIiIhIl0QUOR2clJQUbrjhBnx9fdFqtYwYMYJNmzbVe2xJSQmhoaFIJBLKy8sbHTcyMhKJRHLBz6JFiy44RhAEFi9eTM+ePVGpVISEhPDqq686yrV6caa/tZw+fRp3d3c8PT1b6U3jOMvXzZs3c8MNNxAUFISbmxsJCQl8/fXXjnStXpz5f3v06FFGjhyJi4sLYWFhvPHGG45yq17aytdajEYjCQkJSCQSDh8+fMF7a9as4aqrrsLd3R0/Pz9uvvlmzpw50zqHLoMz/W3v65Qzfa2lva5R4Dx/HXWdEkVOB+f666/HYrGwceNGDhw4QL9+/bj++uvJz8+/5Nh58+YRHx/f5LFffvll8vLy6n4WLFhwwfuPPPIIn332GYsXL+bUqVP8+uuvDBkypNU+NYYz/QUwm83ccccdjBw5slV+NAVn+bpz507i4+P54YcfOHr0KHPmzGHWrFmsWrXKIX41hLP8raysZMKECURERHDgwAH+/e9/8+KLL/Lf//7XIX7VR1v6CvDkk08SHBx8yesZGRnccMMNjBkzhsOHD7NmzRqKi4uZNm1ai31pCs7yF9r/OuVMX6F9r1HgPH8ddp0SRDosRUVFAiBs3bq17rXKykoBENatW3fBsR9++KEwevRoYcOGDQIglJWVNTp2RESE8Pbbbzf4flJSkiCXy4VTp061xoVm4Ux/a3nyySeFmTNnCl988YXg4eHRAi+aRkfw9XyuvfZaYc6cOc06pzk4098PP/xQ8PLyEoxGY91rTz31lBATE9MiXy5HW/oqCIKwevVqITY2Vjhx4oQACIcOHap7b+XKlYJcLhesVmvda7/++qsgkUgEk8nUat/qw5n+tvd1ypm+1tJe1yhB6Bj+nk9LrlOiyOnA2Gw2ISYmRpg/f75QVVUlmM1m4d///rfg7+8vlJaW1h134sQJITAwUDh79qywadOmJt8YAgICBG9vbyEhIUF44403BLPZXPf+v/71L6Fnz57C4sWLhcjISCEiIkKYN2+eUFJS0lbuOtVfQRCEDRs2CN26dRMqKira/ALibF8vZvjw4cLf//53R7hWL87096677hJuuOGGC87ZuHGjAFwwt6NoS1/z8/OFkJAQYd++fUJGRsYlN4b09HRBqVQKn332mWCxWITy8nLh1ltvFcaPH+9wP2txpr/tfZ1ypq+C0L7XKEFwvr8X05LrlChyOjhZWVnCwIEDBYlEIshkMiEoKEg4ePBg3fsGg0GIj48Xli1bJgiC0OQP2Jtvvils2rRJOHLkiPDRRx8Jnp6ewsKFC+vev++++wSVSiUMHTpU2Lp1q7Bp0yYhISFBuOaaa9rEz1qc5W9xcbEQFhYmbNmyRRAEoV0uIM7y9WK+/fZbQalUCsePH3eIXw3hLH/Hjx8v3HvvvRecU/vkmJSU5DgHz6MtfLXZbMKkSZOE//u//xMEQWjwxrB582bB399fkMlkAiAkJiY26am6NTjLX2dcp5zlqzOuUYLg3M/y+bT0OiWKHCfw1FNPCUCjPydPnhRsNpswdepUYfLkycL27duFAwcOCA888IAQEhIi5ObmCoIgCAsXLhSmT59eN3ZTbwwXs2TJEkEulwsGg0EQBEG45557BEBITk6uO+bAgQMC0Oyl4c7g70033SQ89dRTde+39ALSGXw9n40bNwqurq7Cl19+2WxfO4u/jhI5zvb1nXfeEYYPHy5YLBZBEOq/MeTl5QnR0dHCE088IRw8eFDYsmWLMHr0aGHs2LGCzWZrsq+dxV9HXac6g6+OukZ1Fn/PpzXXKVHkOIHCwkLh5MmTjf4YjUZh/fr1glQqFSoqKi44PyoqSnj99dcFQRCEfv36CVKpVJDJZIJMJhOkUqkACDKZTHjhhReabNPx48cvuDC88MILglwuv+CYmpoaARDWrl3b5fz18PCoG/PicZcsWdKlfK1l8+bNgpubm/DJJ580eazO6K+jtquc7esNN9xwwTm1KzUymUyYNWuWIAiC8NxzzwmDBg264LysrCwBEHbt2tVkXzuLv466TnUGXx11jeos/tbS2uuUHJF2x8/PDz8/v8seV1NTA4BUemESnFQqxWazAfDDDz+g1+vr3tu3bx9z585l27Zt9OjRo8k2HT58GKlUir+/PwDDhw/HYrGQlpZWN05KSgoAERERTR4XOoe/u3btwmq11r3/yy+/8K9//YudO3cSEhLS5HE7g69gT8+8/vrr+de//sW9997b5LEupjP4m5iYyLPPPovZbEahUACwbt06YmJi8PLyavK4zvb13Xff5ZVXXqn7d25uLhMnTuTbb79l6NChdXNfPK9MJgOom7updAZ/HXWd6gy+OuoaBZ3DX3DQdapF0kikXSgqKhJ8fHyEadOmCYcPHxaSk5OFxx9/XFAoFMLhw4frPae+pcI9e/YIMTExQnZ2tiAIgrBz507h7bffFg4fPiykpaUJX331leDn53eBgrZarcKAAQOEUaNGCQcPHhT2798vDB06tE0DGJ3p78W0R3aVs3ytXfp95plnhLy8vLqftgwqd6a/5eXlQkBAgHDXXXcJx48fF7755hvB1dW1VStYzvD1Yupb4t+wYYMgkUiEl156SUhJSREOHDggTJw4UYiIiBBqamoc6WYdzvS3va9TzvT1Ytoru8pZ/jrqOiWKnA7Ovn37hAkTJgje3t6Cu7u7cNVVVwmrV69u8Pj6PmC1r2VkZAiCYN+zHjp0qODh4SG4uLgIcXFxwmuvvXZJzEZOTo4wbdo0QaPRCAEBAcLdd9/dpjdCQXCuv+fTHhcQZ/k6e/bsevfgR48e3Uae2nHm/+2RI0eEESNGCCqVSggJCREWLVrUFi7W0Ra+XkxDN8IVK1YI/fv3F9zc3AQ/Pz9h6tSpwsmTJx3gVcM409/2vk4509fzaa/AY2f566jrlEQQBKFla0AiIiIiIiIiIh0XseKxiIiIiIiISJdEFDkiIiIiIiIiXRJR5IiIiIiIiIh0SUSRIyIiIiIiItIlEUWOiIiIiIiISJdEFDkiIiIiIiIiXRJR5IiIiIiIiIh0SUSRIyIiIiIiItIlEUWOiIiIiIiISJdEFDkiIiIiIiIiXRJR5IiIiIiIiIh0SUSRIyIiIiIiItIl+X8jn9wdAxkv8QAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"displaying where these highly used split units are, and their associated HDs\")\n",
    "for u in range(nUnits):\n",
    "    if HDweightSplit[u] > 0.05 :\n",
    "        print(\"u, total use\",u,unitUse[u])\n",
    "        plotPoly(unitGeom[u])\n",
    "        for t in popHDlist:\n",
    "            if splitUnitNo[t] == u:\n",
    "                plotPoly(HDCP[t].buffer(0.01))\n",
    "                plotCenter(len(HDunitList[t]),HDCP[t],8)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "ebe56adb-cc87-4e72-a7ff-6230e6db2168",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are two cases -- either the HD is contiguous or discontig without the split unit\n",
      "here is the list of HDs with split units where the split unit is needed to bridge the HD\n",
      "[8741]\n"
     ]
    }
   ],
   "source": [
    "print(\"There are two cases -- either the HD is contiguous or discontig without the split unit\")\n",
    "splitHDlist = list()\n",
    "for t in popHDlist:\n",
    "    if hasSplitUnit[t] == 1:\n",
    "        splitHDlist.append(t)\n",
    "bridgeList = list()\n",
    "for t in splitHDlist:\n",
    "    nonUseList = getContigFromStarter(homeU[t],list(set(HDunitList[t]).difference({splitUnitNo[t]})),unitNbrs)\n",
    "    if len(nonUseList) + 1 < len(HDunitList[t]) :\n",
    "        bridgeList.append(t)  #the split unit is needed to bridge the HD\n",
    "print(\"here is the list of HDs with split units where the split unit is needed to bridge the HD\")\n",
    "print(bridgeList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "c2ec616c-cce1-4568-9f63-66989759342b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = 8741\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u])\n",
    "    plotCenter(r3(unitPop[u]/aDP),unitGeom[u])\n",
    "    if u == splitUnitNo[t]:\n",
    "        plotPoly(unitGeom[u],2)\n",
    "plotPoly(HDCP[t].buffer(0.01))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "340ff3fe-fc86-43c9-adef-61fcf39837ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now we need to create the vtd topology\n",
      "working on vtd connectivity for unit 0\n",
      "working on vtd connectivity for unit 200\n",
      "working on vtd connectivity for unit 400\n",
      "working on vtd connectivity for unit 600\n",
      "working on vtd connectivity for unit 800\n",
      "working on vtd connectivity for unit 1000\n",
      "working on vtd connectivity for unit 1200\n",
      "working on vtd connectivity for unit 1400\n",
      "working on vtd connectivity for unit 1600\n",
      "working on vtd connectivity for unit 1800\n",
      "working on vtd connectivity for unit 2000\n",
      "working on vtd connectivity for unit 2200\n",
      "working on vtd connectivity for unit 2400\n",
      "working on vtd connectivity for unit 2600\n",
      "working on vtd connectivity for unit 2800\n",
      "working on vtd connectivity for unit 3000\n",
      "working on vtd connectivity for unit 3200\n",
      "working on vtd connectivity for unit 3400\n"
     ]
    }
   ],
   "source": [
    "print(\"Now we need to create the vtd topology\")\n",
    "vtdNbrs = [list() for v in range(nVTDs)]\n",
    "for u in range(nUnits):\n",
    "    if u%200 == 0:\n",
    "        print(\"working on vtd connectivity for unit\",u)\n",
    "    for v in muniVTDlist[u]:\n",
    "        possibleList = muniVTDlist[u].copy()\n",
    "        possibleList.remove(v)\n",
    "        for uu in unitNbrs[u]:\n",
    "            if tractGeom[v].intersects(unitGeom[uu]):\n",
    "                possibleList += muniVTDlist[uu]\n",
    "        for vv in possibleList:\n",
    "            if isRookAdj(tractGeom[v],tractGeom[vv]):\n",
    "                vtdNbrs[v].append(vv)  #we catch the complement in another loop\n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "9fdf9026-7d49-419a-a4db-55cc8f72e815",
   "metadata": {},
   "outputs": [],
   "source": [
    "tractCP = [tractGeom[v].centroid for v in range(nVTDs)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "cf287ba6-b50f-4ad3-890f-41b3c7be1f13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final pop = 120524.0 = 120524.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final pop = 121426.0 = 121426.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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WombMWvdzua79GVBy1NkkqAxQDue9DxI3DSSpEUK0qIAf/SSawymSgJRzYMTdsOpx6HkhJPZumbAawlVTE9HOt3F4W3iC8+YHpKZGCNHS3KOf/KT5qVELWgofOVnv0wsegtiu8PEfwWFruZjqq7SypibMPxKAelPqVCmlH5GkRgjRstyjn/yk+UmSmkARFAoT5sORn+F///R1NDW5amr8pFYjEDmbnyStEUK0HPfoJz9pfpKkpjWobx+UzoPh3Bnw3d/hyE/NG1NDuZKaMFneApyTSBYVeXlOGSWjn4QQLcs9+slPJt+TpKZVqccn1qgHoN0Z8NEfwW5t/pDqq6RyBumwON/G0Vhe7tyckZFBZGTdSy00hlbl/0II0RJ0TUdDk6RGNBOzBSbOh9xd8O2Tvo7mhPzfnPehrS2paZ6qD03TyM/PB5wzZj/yyCOMGDGCbt26MWfOnMaViZLmJyFEi1Mo3t/5vq/DACSpaSUa+O07qS+cPwu+fw4y1zdPSA1Vlue8b4XNTy2RJuTn57N27VrS09N56qmnOHToUKPKMZTU1AghWl73GP+Yf0ySmkB19jToOMjZDFVR6ttYqjaDtdbmp2Z23XXXAZCQkED37t3Zt29fg8uQId1CCF+IDIqkV6x/LH0j89T4UkUp/PoJFB2unLjNNYGb4VwjyfXYWug8XmtADmoyO5uh5o+EVbPhor83z2uoD9dwbmiFzU8tIyTkxLIKJpMJu73h7dPOOhpJa4QQLcukm/xm9JMkNb7isMOiS+DQJgiNdS5voOmVN9dj7cS29v2c6zs1RMJpkPYYLJ8JvcdDt1HN8lJOqeoSCa2tpsY9N5D/N+toSqFa5WzNQojWzKybsRn+MT+aJDW+cmw3HNoIV/0H+lzWfNcZegds+ww+vhvu+gGCvTvipl7KqtTUrH7KOTmgqxbKo1bKAWgw/K7KVadFQ0kDlBCipZl1s9+MfpKkxldcVXWRHZr3OroOE16El8+Br/4Clz3fvNerjaumJrIjbH4LLOEnaqOq1lDpJsjaAtGdod3/tXycLUhVmR16//79Hvs2bNjQqDI1DVrT/MdCiMBg1iSpEa4PtZZoLohNgd/Ngc+mwxmXwmkXNv81qyo95kxiZvx66tf7zBngJ/84XFpLmqApA0OTmhohRMvyp5oaGf3kMy3cV2PwZOgxBj6Z6tlxtyWUHncO5a5PAmcyg6Oi+WOqtxZMPptI00DJkG4hRAsz62a/6SgsSY2vuGtqau4qLy9nwoQJnH766QwYMIALL7yQ3bt3A/C3v/2NXr16oes6H3/8scd5U6ZMcZ9zzjnnkJ6e7t438YorSH1qB6nP7iP1zNPQdZ1ly5Y116vzVJYHoTH1O9Zk8bOkpvWMJ9KU9KkRQrQ8f6qpkeYnnzl5Tc3tt9/ORRddhKZpvPDCC9x66618++23pKWlcc0113DzzTfXOGfixIksXLgQs9nMZ599xh/+8Ad3f42PPvrIedBPS9jw4i2MWxzMuOg9sOYZMAxnk49hd/b1CYmB4XeCOdg7L7W8wFlmfZgs/rnKeKugpE+NEKLFSZ8acUItzRohISFcfPHF7ufDhw/n6aefBmDo0KF1FnXZZSdGUQ0fPpxDhw5ht9sxm6u8zf2v4tV9D3F9nwNYvn/G2dyjB4FudnbU1U2QfwC+ftzZYdeoHJVkOE7cV31c9d41HL3H+TBp6YlrlhdASHT9fh6mIElqGkkm3xNC+IIM6RYNmv/kueee4/LLL29Q8c899xwXX3yxZ0IDlJWX8276UdZ8vgzOGVv7yT8thoPpzuHfWmWio5kotzm45q/v8Ov+HEJDgkiMjeXlBybRs2sSf3vjSxZ99j27MrP58JoVTJh0orgpL67h+z35hD41gIiICObNm8dZZ53l3v/SSy/xr3/9C7PZjJ6/n3XP9iGklrB8osoopYPF2czf9SNxQQ37Z6OA+/uO93JgtdEkqRFCtDhpfhLUt6fG3/72N3bv3s2qVavqXfJbb73Fe++9x+rVq2vse//99zn99NPpV1dCAzDgGuetuvJybp+V6tks9sL7zmYx1Z9r7k/g5j9cBOqwx2kTz0pm4R1nY75+cY1msU8++YS3336bH3/8kejoaI4+N4ag4ztg/cITExBSOQmhOdg5essSXu+fhddoGsfKCxgRl8j4riMadOozWz9vpqA8SUojhPAFf+ooLEmNr9RjSPfTTz/Nhx9+yMqVKwkLC6tXsUuWLGH27NmsWrWK9u3b19j/6quvcssttzQq5Po1i2nOpiil3K/tsmHdoKLYfU7VZrGnnnqKRx99lOhoZ/NUu9MGwcY3YPks54R8VC4d4aKbod/vGxW/N2j1qFlLTU1lzZo1REY6JzrsERbuTmyqn51ZbuXZwRPRvDC6SpqfhBC+IDU1glN1FH722Wd59913WblyJTExMfUq8b333uOhhx5i5cqVJCcn19i/e/duNmzY4LVRT7U2i7nWp3LYwGxxPo5IhP273OdUbRb79ddf2bBhA7Nnz8ZqtXLjjTdy78NHa17MYYfH48Fe7pXYG8NA1Sv5yMjI8Hg+ofvoOo999pcvUcqBpjX9n6IGGNJRWAjRwqSjsKiS09T8EDp48CD3338/3bt35/zzzwcgODiYdevWMWfOHObPn8/Ro0fZunUrU6dOZfPmzbRr145JkyaRlJTkkWisWrWK+Ph4AF577TWuvPJKoqKimhx+nc1irtez4wtnrYphh/JCOL6Xt958s0azmN1uZ9++faxevZq8vDzOO3so3Qt/5JJhPSs7JdtP3IPzcYs6UfdRdRbgk9E0jby8PGJiYkhJSeHGG29kxYoVZGVlccstt/DQQw9VKV6hNWSh0pNdl9Yz/FwIETjMupkye5mvwwAkqfGhumtqOnfuXOcH6EMPPeT5oViFzXby3ud/+9vfGhRhXU7aLGaqrJ1ZepPH5iU7g5j95l9Zteprj2ax5ORkrr32WkwmEwkJCVx8WhA/rlzGJVGnVY7IMp/orNxlWMMX9fQyvRE1Ifn5+axdu5bc3Fx69OjBlClT6NSpEwBnJ3Ti2V++xK40uoeF8IceFzQ6Nk1J85MQouVJ85No2WUSvOiUzWIh0TBhPlwyzp2MvPfhMh56+/Fam8Wuu+46li9fzgUXXEBZWRnfbsvhgcsHwb01Ozn7Sm58EM9u/YIKZXBV8oAGn3/dddcBkJCQQPfu3dm3b587qRmeNIDhSQNwKMUzWz6j3G4lpJHzAzl/kyStEUK0LLNuxq78I6mRGYV9rvUkNa5msfz8fM4//3xSU1MZNmwYAHPmzKFz586sXbuWW6fOoHPvQRwtNSA0hkmTb6G8vJzLL7+c1NRUUlNTOXbMucjljBkzyM7Opk+fPgwZMoSL+ifyhxEpPnyVNV2b+ykz+l7MzH6X0D26S4PPDwk5MUDdZDJht9f8x2/SNNqFhPGXjCaMlNLc/xNCiBYjNTWC1rSmkEtzNIuFhISwaNGiExvevBy/+mBWLTdH75TTx/D8L5+TZy0mNjiiUWUYpz5ECCG8yqSZ/CapkZoaX2nA5Htti//9PFqyQWdSt2Es2v19o87VUMh6lkKIliY1NYLWWFPTIjTdc16aVqhqbZZrkkGXDRs2nPTc+LAEDFVBnrWU2OD6zU3kIvPUCCF8IUgP8pukRmpqfEVqamqn6bT1zq43dR/Got3/a/B59ZkYUAghvE1mFBa09Q/uOmm6cxFNP1I1VSgo3EJ29jLKy4/UmIjPbI7mjN5zmny9+LBEDGUlv6KMGEto/U9USibfE0K0OFnQUrTaId3NzhQEjgrfXLu8AI7vg7x9qGN7KT76G8e3fsNvQyI4vuUuAEJDutAhaSKRkX1qnL5l6z1eC+XGbkNYtPt/TOtzYb3Pca79JMmyEKJlBUyfmrlz5zJr1iymTZvGvHnzAFiwYAHvvPMOmzZtoqioyD2z6smsXr2ap556io0bN3LkyBE++ugjJkyY4HGMUopHH32UhQsXkp+fzznnnMPLL7/Maaed1pSX4EPS/FQrk8W9TpTXGQYUHYG8/ZC3H1vuPvJyDpJ37BiFRUUYtlL3oZo5lIiISGK7jaCsMIxR/eY1T0x1SAjvgMPYQJ61iNjgyHqd45xRWH6fhBAty59GPzU6qUlPT+eVV16hf//+HttLS0sZN24c48aNY9asWfUqq6SkhAEDBnDzzTdzxRVX1HrMP/7xD55//nkWLVpEt27dePjhhxk7diy//vqrxzwgrY7U1HgyWZzrRjVWeaE7aVF5+ynOOUBebjZ5BYWUlxRBlQmigoLDiYmOJLF9Ij37nYUpoTvEdoO4bhAa635vfv7vC40KpfrClg01ucdI3tj9P+4786J6Ha9p0lVYCNHy/GnyvUYlNcXFxUyaNImFCxcyZ45nH4Lp06cD8O2339a7vIsuuoiLLqr7D7dSinnz5vHQQw+51zV68803ad++PR9//DHXXHNNg1+Dz9VzHaE2x2Q+efOTww6FB92JS0XufvJzDpGXd5zCohLP2hbdQkREBLGxMZzeuw+h7VIgtvIWkwxBDeivUi+eCWr1hS0bKi40lhDNYHvBEXpHd6jH1VWNGIQQorkF6UE4Wnxdvto1Kqm5++67GT9+PGlpaTWSmuawb98+srKySEtLc2+Ljo5m2LBhrF27ttakxmq1YrVa3c8LCwubPc6GkT41tTJZwFoMhzY6a1uO76f46AHycnM4XlCEtbSYE1PMaQSFRhITFUliUkd69u+CKb47xHR1Ji7hCV75+TrsJY06ryELWxYV70DXgggP7+7eVlGRz8Ci+SzaPoEZ/a+kXWjMKa4oHYWFEC2vVfepWbx4MZs2bSI9Pb054qlVVlYWgMdCiK7nrn3VPfnkk8yePbvZY2s0V03NkZ+gKNu1sUoNjqpyXC2PzSHQeSjogTEq3263s3v3bgqPRaCOWmDhfYCrb0sEsbGx9O7Sk5CqtS3RXcBsaYHo6lerFhratUZn4V9+fYCoqBBstuPs2fMJCxaOIi+vjPEXP87wEXto3945c7DZHINhlHFmn6cBKCrazr79z9Ol83U8nHg5c7b8l0f7X0TwSdaFcvapkRpAIUTLMmutNKnJzMxk2rRprFixwu/7scyaNYsZM2a4nxcWFtKlS8PX7Wk2IVHO+6WTG1/GTZ9Ct1FeCcfX8vLysNvtDJl4N/rBsyCmizNxCY31dWiYzPVbsqBnj/urbXmBM/v8g5iYGIKClnHPPa/Qr+9w57E9NxISfAv9+o4EwG4v4uef7+LXX/+EzV5ISHAHTj/tUUJCnIn8Pb3O4e+/fMVD/S5BryOR1RQoqfkTQrQwV58apVSNqS5aPJaGHLxx40ZycnIYNGiQe5vD4WD16tW88MILWK1WTCaT14NMSkoCIDs7mw4dTvQtyM7OJjU1tdZzgoODCQ5u3GrHLaLjQJj2M9jLKzdoVZpKtJrNJpqGu79ESS68mga2cgKFyWTCYrGgRyVBn8vqfV5TO+PWj3dqP062sKWuBxMSkkT37jMICanZf6ZDeDsu6diL+TtWcNcZY2stX5NaGiGED5h05+e+XdkJ0oJ8GkuDkpoxY8awZcsWj21Tpkyhd+/ePPjgg82S0AB069aNpKQkVq1a5U5iCgsLWbduHXfeeWezXLNFxHZt3Hlm/64lawyz2YzD0fCOZk3tjFs/zf/NQ9ct9Onz1EmPGdSuF4dLcvl4//dMSDmnxn6poxFC+IJZd6YSDsNBkO7bpKZBHTIiIyPp27evxy08PJz4+Hj69u0LOPu/ZGRksHv3bgC2bNlCRkYGx48fd5czZswYXnjhxDDZ4uJiMjIy3B9Q+/btIyMjgwMHDgDODpfTp09nzpw5LFu2jC1btnDjjTfSsWPHGvPZtCkB1NRgNps9ai7qS9M08vPzAUhJSeGRRx5hxIgRdOvWrUU6sbe0S1LOIae8mLVZW2vdL3U1QoiW5kpq/KFfjdd7mc6fP5+BAwdy2223ATBq1CgGDhzIsmXL3Mfs2bOH3Nxc9/MNGzYwcOBABg4cCMCMGTMYOHAgjzzyiPuYBx54gHvuuYfbb7+ds846i+LiYpYvX+73fXuahXuNjRNJTXl5ORMmTOD0009nwIABXHjhhe7E8m9/+xu9evVC13U+/vhjj6KmTJniPuecc87x6AC+a9cuzj//fFJTU+nduzf3338/RjMtYdDYpKa6/Px81q5dS3p6Ok899RSHDh3yQnSNo5RyTzy5f/9+j6bSDRs2MHr06EaVe3vvsaQfO8B/dq2i3H6iCVJmqRFC+IKryckfkhpUG1FQUKAAVVBQ4OtQmu7npUo9GqXU0V3uTWVlZerzzz9XhmEopZT617/+pc477zyllFLr1q1Te/bsUeedd5766KOPPIr65JNPlM1mU0op9emnn6quXbu6911++eXqueeeU2VlZeqSSy5RFotFdevWTaWlpaldu5zXfuKJJ9Tpp5+uNE2rUfbkyZNVv3791IABA9SQIUPUypUr3fuqn2e321V6enqDfxSAysvLU0op1bVrV7V27Vr3vtTUVLVmzZoGl1nd8q/+1eQymsPOvAPqHz9/pv7+86dq+/G9atI716ir373G12EJIdqYbw98q/q+0VcdLT3aLOU35PM7MMYDtzUb34Cu50BCT/emkJAQLr74YnfP8+HDh7N//34Ahg4dSvfu3WspCC677DLMZrP7nEOHDrlrTDRNo6CgAIAbbriBlJQUPvjgAy6//HJuvfVWANLS0vjyyy8ZNarmKKx//vOf/Pzzz2RkZLBgwQL+8Ic/uGt6qp9nMplqrQVqaM3QyTrjBprTYrrwp37jufeMC9l47DfsMT2I0Qp8HZYQoo0JqeznWWYr83EksqBl63N0B+xfA1e+etLDnnvuOffsy/X13HPPcfHFF7uTnHnz5nHppZfy8ssvk5eXx8MPP8zAgQNxOBw8/bRzPpWhQ4fWWV7VNb9cyZHLyc7Lyclh7969gLNZrbHNNN7j3406IeZgrus5mh3p/4c9cLpZCSFaiZjgGADyrHl0wbdTp0hS09pseB3CEuCMS+s85G9/+xu7d+9m1apV9S72rbfe4r333mP16tXubS+99BLXXnsts2bNIicnh/PPP5+zzjqLN998s94J08yZM1m6dCl5eXl88MEHdc6x4nA43Pu2bdvGeeedB8C6devq/RqaT+vIFDTpVSOE8IG4kDgA8srzfByJJDWtS0Up/PQODLkZ6phZ9umnn+bDDz9k5cqVhIWF1avYJUuWMHv2bFatWuUxa/OLL77Izp07AUhMTOTiiy/miSeewGq11jthmjt3LnPnzmXlypU88MADfP/991gsNWcBLisrIyQkhKNHjxIdHe3erus6+fn5NVZ6V0phtVqpqKjAblXYrA727t2Hrp9IQDZs2FCvGE8l12olPedXlDIwcDaJ2ZWBXTmwGwYOZWAzHNgNBzZlYDMMDKWwKYMKw4FSigrDQAFGZdKho2Gg3PeGAcX7y4jU7Zh1Hb3ayDalFDbDICEijPZRUei6jq7pBJvN6CYTZl2nvCIezXLMK69ZCCHqKyYkBoDj5cdPfmALkKSmNfnlQ+cq1IMn17r72Wef5d1332XlypU1koC6vPfeezz00EOsXLmS5ORkj33du3dn+fLl3HzzzZSUlPDuu+9isVjYtGlTvRMml7S0NKZOncqWLVsYPHhwjf3l5eXYbDZ27NjBOeecmINl8ODBbNmyhR07drj7CymlUEoREhKCYRj88r+DxLQPxeFQKMM5o6VSjRvx7izbwGIJ5uI/jEbXdbYb3UisKEXH2c9IRyNIN2ExBROkmdB1HYtuIkgzE6SbMetmTJqGxWQh2BSErpkI0s2YNN09SVV1OcXlPH10P7PH9D5pfIeOHyGvKB+HcuAwDCrsNgzDoMJm41BxMjZT/WY/FkIIbwnSg4gMiiTPKjU1oiHS/w0905zLB1Rz8OBB7r//frp37875558POGdVXrduHXPmzGH+/PkcPXqUrVu3MnXqVDZv3ky7du2YNGkSSUlJHs1Jq1atIj4+nkWLFjF16lSee+45srKy0DSNn3/+uV4Jk81m47fffqNnT2dn5vXr15OTk1Nnh2Wr1cqvv/7KNddc4zHNtq7rDBgw4KTXCipMpN/oznXub8ysw/t2HuSTd1agaRrtzYlc2HnISY9v6szG9V3eoFNcBzrF1b5i96Lv/47VaJ4JMIUQ4mRiQ2LJL8/3dRiS1LQaR3fA4c1wzTu17u7cuTNK1d6f4qGHHvJYEboqm81W5yUHDhzI999/z8GDB+nSpQvdu3fnggsuAE6dMIWHh3PTTTdRUFCA2WwmPDyc999/n9hY51pO1c8LCgri2WefbZZZqRsz63C30zvT7XRnorTgk+3Nco3qmrxmigaqlfT/EUIEltiQWL9ofpIh3a3FcedoIDoObPFLuxKmPXv2uGd+dnXgfeihhzh48CBWq5Xc3FwOHjxIu3btCAsL4/vvv2fr1q1kZGTw/fffuxMicI5wMpvNVFRUsHLlSr7++msSExP54osvGDRoEKmpqfTt25dFixa5z0lPT+ecc85hwIABpKam8vXXX7v37dq1iwsvvJABAwZw5plnsmTJEve+lph12B9mNtaossi7EEK0oNiQWGl+Eg0Qnui8LzkKUR19G4sX/P73v+eBBx5g5EjnKtVWqxXDMLj++uv59ttv6d+/P/v376d3795cccUVREREMHHiRN544w3S0tLYuXMnaWlp7NixA4DJkyczZcoUbr31Vo4ePcqQIUMYOXIknTp1qnFt16zDubm59OjRgylTptR6XFM09Br7C8uICWnaP0cdqakRQvhGXEgcu/J2+ToMqalpNVwdTB2BMZncqFGj6Nz5RD+YiooKunTpglLKXeNRWFhIfHw8wcHBHDt2jKNHj5KWlgbA6aefTkxMDF9++SUAP/30ExdffDEA7dq1Y8CAAR61NVVdd911ACQkJNC9e3f27dt38mAbUfvR0Gu8sfkgU4d4dtROTU2lqKio3tfUUFJTI4TwidhgaX4SDeFqforr5ts4mlHv3r15/vnnueyyy+jatSsjR45k0aJFWCwWEhIS6NChA++99x7gbIrasWOHe9bkwYMH89ZbbwGwd+9efvjhB/e+6lpi1uGGXkMBkRbP1W0zMjIa2PFYammEEL4RGxLrF/PUSFLTWpQeA90MobG+jqRZKKWw2+28+uqrPP7443zwwQe89NJLXHfddRw9ehSATz75hNdee42BAwfy3HPPMXLkSPfsx4sWLWLdunWkpqZy3333MWbMGPe+1qrh/XRk6j0hhG/EhsRSai/F6rD6NA5JavzAvffeS0pKCpqmeYyi8eg0e/XDLPrF5J585WQrb59sn79yvfbDhw8zdepUBg4cyFVXXUX79u3dHYIHDBjA8uXL2bx5M2+99RaHDx/mzDPPBHCvS5WRkcEnn3xCQUGBe19rUJ86llOtQK5rmiQ1os366ehPbMzeSHZJNoZq2Jpxoulig51fuH1dW9O6v8r6i4MbIHM9oEAZziEoyqj23PXY4bw3HO7nv0/O44HHL2bk/70Na56BzHiU4eD66xfy7eOX0z85hv0/fEjv545xRVERkZGRpKWlcc0113DzzTfXCOdk+/xZly5dOHLkCNu3b+eMM85g3759HDx4kK5duwJw5MgROnRwztGycOFCwsPDueCCC9j63SGys7Np164duq7z1Vdf8euvv7r7tVQd6l69Scpbsw63xDVq66dTtfOxpklNjWibDGUweflk7IazmdeiW+gU2YlOEZ1ICk8iIyeDYFMwV/e6msHtB9MxoiNmXT7+vKnqUglJ4Uk+i0PeVW/49knYvQos4aDpgOasUdG0as9Nzg6/mn7ippsYFaJDoQnsVsjaApYoQEdTDvKP7IWoeAqjehMfu5XgYOfyCCdbEPJk+/zFHXfcweeff05WVhZjx47FYrGQmZnJggULuOqqq9B1HcMweOKJJ9yJzIIFC3j77bdRSnHGGWfw0Ucfued2+fTTT5k7dy4mk4mOHTvyxRdfEBoa2uQ4G7pKeHM6VT8drcr/hWhLlFLYDTt3DriTM+PP5GDxQQ4WOW+/5P5Cp4hOlNnLePSHR1EozJqZTpGdSI5MpmtUV5Kjkuka2ZUuUV3oGN6xzpm/W/o1KdSJe5TzezLVtld+oap+rHt7tW2urz5KKXeNVruwduha0xpuYkOkpiZwJI+AAz/CA/vAXHNdo3p7KgX+8AakpqIBS3qs5IprriE8PIe8vDw+/PDDWtdNao1eeeUVj+fr168H4Nprr+Xaa691b8/JyaGkpASARx99lEcffbTW8m699VZuvfVWr8epFK0qT5DRT6ItMukmQkwhRAdHc16X8+o8Lrcsl115uzhQeIDfin7jQOEB/nfofxzccdBdy2PWzSSGJlYut1JLQlCZWBjK8EgQ6jqutmSiPslKS5py5hRmDJnRpDJcK3XnW/ObHlATSFLjDV3Phq8fh+N7IPEMrxRpt9uZM2cOH374IaNGjSI9PZ3LLruMLVu2kJCQ4JVr+IxSkLe/somukrWk1kNdNTbVWffuJf+DDwjq2JH8TYUw+s5mCdVhqBqLSzaHCoeBYRh1rmJeHxoyT41ouyItkRRWFJ70mITQBBJCExjRcYTHdrth50jJETILM/mt6DdySnMA0Fz1n5qGhlbzvto21znV99fYfqpj6yi/6n1dxzn/qxlnrds1jWc3PMux8qYvhOtqznMoR5PLalIcPr16oHCtmG14b2iwq9PsqFGjADjrrLPo3Lkzmzdv5sILL/TadXzi5yXw0R2e27TBMHw4BHk2GdWV1BhlZUSmpRE2cCBBhz9qtlCtdgOTufkThQEdovnuYB7nJ8e7tzW0n44zHZKqGtE2RVoiKbSePKmpi1k30yWyC10iu3A2Z3s5Mv/26pZX61xipyHcCw77+G+QJDVeUfmh58W6f1en2W3btnHGGWewe/du9uzZQ69evbx2jQbZ8zV8cCtUlILJAinnwFm3QvfRJyYGrK/8A2CJhOsWO5/vXgn/+7qy/5GnupIaFGinqNWousjk+mc+xjDqfn/CYsPof+vYGtuLKhzkO5q/X01imIXj5U1PiqWmRrRVMcExfjFNf2ujazoGTf8bp1d+rXIYUlPT+rk/jBuX1FTvNBsZGcnu3btrdJp94YUXSE52zjp7spW3T7av0fL2O+fKGTcXKkrgl4/grSucc+fo5hMdn6nsHO3qJF3jpkFxNnQ7D1KcSySQs83ZidpV41WFyWSqI6lR7uHtdf3Yqw6PNwzF8D9NrPPl/fhU7bU9JhQJwUG17qtNU1frbooWaCUTwm9pmkZ6VjpTV011900xMPg552euPP1K7h9yv69D9EsmrY6/sQ3k6mgsNTWBwP3h2rhfjOqdZl2qd5qt6mQrb59sX6MFhTnvB0+BoBA49344tNG5crh7uHpdt6r7HRDRHlKvcxetrEXO2p9a1FlTU0VIVAhFB48S2dkzadM0jby8PGJiYpj45B3cVrSZFStWkJWVxS233FLnz2j3R99TlldK76vPdcbQgGShKat1e6MKWDoKi7bq0u6X8m3mt6A5aw00zdlnpMhWxNKdSyWpqYOmaV6pqXH10/H1HEGS1HiF95uf/I4rqbGVOpMaTYPOQ5y3JrKVFaPMIbXuq09Sk5SaQtb6HTWSGg8KcjIP17rIZNXy83Zkkrsrh54XpbL5la+wlpST56hgjvnEMc4Ouc5b9Xzn4QtO58/LNhAaEcUz155P6u8msGfj9xQdz2XwRb9H6z+RnqfH1Ti33G4wfUTKSV/nqWiaJs1Pos268vQrufL0K2ts/9u6v7Eh2ztzRQUiXdO9loh4s6zGkqTGG9z1/m0kqSHOq0WXl5ViN9U+p8xJk5rKJDKqexK7V2zl+N6aTUgb/vUZEcHhmCwmJt/hHPJd2+R1FaU2fvzHR1jCLZx136WYgswk9OtGycEcEj9cSa/zT6vXa3kY+NO5PYiJieHfIWb6xeh888tmdyJ1V/+LePLivvUqq+EUMqewECcUWAtYdWAV/RP6+zoUv+XNRETTpKYmQJy8b0dAsLiSmjKvF223ltAupPbOZUFBQRQXF9ey50SfmrDEWEY+/Ieah/wJhtxzCTExMZhfuq/Oyet0XWfUo1fVen2ljIa1P1VTfRbgYzmHTnFGU0lNjRAuc36cQ5mtjAeHPujrUPyWN5Mak2by+ZBuWfvJG1z9QawFvo2jObmGWlfUPp9MU1SUlxNsqb0zrq7rREZGUlBQ7WdbtaNwc1LQlESheiKFj0cGCNFWPLvhWZbvX86DQx/06bT9/k5H90p/PqDJsxJ7JQZfBxAQ4ntAdDJsed/XkTSfoHDnfTPU1FRYy7EE1xz55NKuXbuaSY1h0BK1EspQaE2oqWlxqhXFKkQz+e/+//L6L68zNXUql/e83Nfh+DVvDekG5+R+MqQ7EOgmGHwjrH4Gxv4NQmN8HZH3uWpqbN6vqbFaKwiPjGr4iaeoqfHGIpO2cjulRd6bVNFuGLz43tbKkRmcuMd1X2Vb5U0pKCixUVxu53B+GTeN6cGw/u1rFq4p6Sgs2rwjxUd45IdHGJM8htv73+7rcPyeruleS0R0TZch3QFj4A3w7VznbLnD7jj18a2NpbKmpqLU60VX2GwEh4TVus9ms5GVlVVjjh2lWubj22SG8Ji6a5GqO1UiVV5hp7TUjqEq59EwKkdSGZXrvhhgKNdicyfKiosOISrCgmEYPPLvTbUnNWjSUVi0eWWOMoL0INYeXsurW1/lhj43EGyq/7/htsa1xpU36Jru8z41ktR4S2QS9LoYNrwOQ28PvJnQ3DU1zdD8ZLNhCXUmTTk5Ofzyyy+Eh4ejlMJkMtGlSxcSExOdlz90CGW3U/LDD8TdeKPXY6nB8G7fnRCLmRBL4//Z6bpOWBPOFyLQdY/uzmcTP2P+T/N5cfOLfLjrQ96++G33KtLCkwzpFnUbMgX+MxH++xCEuv4BqcrOppWZsFLVHjdAgz5c63lsQz+wm6H5yWazE1RZU6PrOp07d+a002ofQn3sjUVEnDuSuEmTMLXArL3OVbr9K0Gtu4uP1NIIARAdHM19g+9jU84mcstyCdLrPyt4WyNJjahbt9HQdST89G7lBq3KB+JJHtdLAz6w6p0s1fM4V3mRHSCue/3jqCfDYSNr9SLivnmauH4T2FPRE3LDnUsn6Cbn8go9LoC4blhSuhJRuchny1CtZpS0piEdhYWoNHf9XHbl7WLRuEVEWCJ8HY7f0jWdvQV7efSHRz1W/3bNygwnVhPXNb3WFcJ1TQcNjpcfl6QmoOg6TPnc11G0OoPTfs+hjFVsyzlIxZZttAv6CfYddA5/Nux8GhbE9j0D6Jx6E2HBBwh7dkaNMpRS7rZhrZaalbq2V90P1DymsIjO5iIOvb27tpMqMwkNdB1N053rYJnMaKYg0E1oJjOaybk+1nFrMKXmeHSTCXOQGVOQCV03oZt1dJMJk8mEyayjm03oJh1TkAlN08jZl83B7bux26xoQFm+iSdePVgjnAO/nYklau9Jf9ZCBKLj5cc5UnyEMxPOBOCDnR+wdOdSZp89m37t+vk4Ov82stNIMgsz2ZW3C6Uq+/ZVrp3lce96XO05ONd7MpRBUngSvWJ9tOhyJU15q4eQnyssLCQ6OpqCggKiohox0ka0jOrzz9grWP1CH7onj6LzFa81uLimLjBZkLePvZv+zcAxT9RZpnI4UIYDZRgoux3DVoFht2PYbeBwYNhtKIeNrM/+juncmTjsdhw2B3a7HcNmRxkGDoeBUXlz2J1lGQ4HSiniOsbTY0gfQsJq70zt8pdXx1B4tIx/zfyhUa9ViNbq1S2vMm/TPP5w+h/4XcrvuGvlXUzsOZGHRzzs69CEFzTk81tqaoR/qZrQlOXzzQt3sb78DJYUaAR9+SJltjJeuez/6l1cUxaYBDCUHU33/GdSvUzNZEIzmZxPTjLIIj86ki4Da36L8d7K3lpraSkTwquGdxwOm2DpzqUs3bmUAe0GMHPoTF+HJXxAkhrhV0p/XcF3qz6jnV7MscIiym0OHrz+fkg+G8wWpn/5YoPKq7pSd0pKCjfeeGO9Vup2qSgvRA/yrCFpapnVNTXxOhGYd4oRorXpE9eHxLBE+if0Jyk8iZv73kyQSToHt0VNmlF47ty5aJrG9OnT3dsWLFjA6NGjiYqKQtM08vPz61XWiy++SEpKCiEhIQwbNoz169d77M/KyuKGG24gKSmJ8PBwBg0axAcffNCU8IUfKtrxHdtybYRGxXB6txQuv+Ov0H00mC1eKT8/P5+1a9eSnp7OU089xaFDp16L6WR9cRpbZvXyXf9OUlJSeOSRRxgxYgTdunVjzpw5DSpLiLZI0zSiLFEkhSfx4NAHaRfW7tQniYDU6KQmPT2dV155hf79PVc/LS0tZdy4cfz5z3+ud1lLlixhxowZPProo2zatIkBAwYwduxYcnJy3MfceOON7Nixg2XLlrFlyxauuOIKrrrqKjZv3tzYlyD8kEmHXpHlnHnDM3S75h/Q/kyvll99gcl9+/ad/IR69OSvd5n17L7WtCSpTXSRE6IGh3L4xdpDwrca9RtQXFzMpEmTWLhwIbGxnhMaTZ8+nZkzZzJ8+PB6l/fss89y2223MWXKFPr06cP8+fMJCwvjtddOdAz94YcfuOeeexg6dCjdu3fnoYceIiYmho0bNzbmJQg/pWsKoxk/l+taqbsuzim/T/7PpD5l5u/agDkuuV4xNjjxcscqRNvlMByYdJOvwxA+1qik5u6772b8+PGkpaU1OYCKigo2btzoUZau66SlpbF27Vr3trPPPpslS5Zw/PhxDMNg8eLFlJeXM3r06CbHIPyHUjr+9vF8quan+ij85mXaXzS1Xsc2NPE6QUPzrx+dEC2qjQzmFSfR4I7CixcvZtOmTaSnp3slgNzcXBwOB+3be65l0759e7Zv3+5+/t5773H11VcTHx+P2WwmLCyMjz76iJ49e9ZartVqxWq1up8XFhZ6JV7RzDTQAuwP09F1ywhJGYLuWmpCCOF1sSGxHC8/7uswhI81KKnJzMxk2rRprFixwuPbZEt4+OGHyc/PZ+XKlSQkJPDxxx9z1VVXsWbNGvr1qzm50pNPPsns2bNbNEbRdBoahheH8TR1pW5VS5+ahpSpDIPyzR/Q5Y43Th1sEwVWKihEwySFJ7G/YL+vwxA+1qCkZuPGjeTk5DBo0CD3NofDwerVq3nhhRewWq2YTA1r00xISMBkMpGdne2xPTs7m6SkJAD27NnDCy+8wNatWznzTGfH0QEDBrBmzRpefPFF5s+fX6PcWbNmMWPGiZlnCwsL6dKlS4NiEy3PpDd8SazmpJSBakLz05EvnidixPUnXT+qqYlXVTKqW7RVwzsMZ/ba2VgdVlmVuw1rUJ+aMWPGsGXLFjIyMty3IUOGMGnSJDIyMhqc0ABYLBYGDx7MqlWr3NsMw2DVqlWMGDECcI6oAmdfm6pMJhOGUfvolODgYKKiojxuwv9pGjj86aNZqUZPaeewluI4vJXYARd6OajaOZd98qOMUIgW1CXS+aU1uyT7FEeKQNagpCYyMpK+fft63MLDw4mPj6dv376Acz6ZjIwMdu92rpXjSoKOHz/R1jlmzBheeOEF9/MZM2awcOFCFi1axLZt27jzzjspKSlhypQpAPTu3ZuePXtyxx13sH79evbs2cMzzzzDihUrmDBhQlN/BsKPONdv8tyWmppKUVGRbwKCRq/SfeSDvxI//k9eDkYIUZsO4R0AOFJypMa+UlspO47voMxe1tJhiRbm9RmF58+f79GXZVTlisqvv/46kydPBpzNSbm5ue5jrr76ao4ePcojjzxCVlYWqampLF++3N15OCgoiC+++IKZM2dy6aWXUlxcTM+ePVm0aBEXX3yxt1+C8CFn+uCZ1VSdcdcnoxsacc2i/VvAsBPWqWUXd/OjOi4hWlT7cOfnRVZJlsf2zMJM7lh5B5lFmYAz+UmJSqFbdDdSoivvo1JoH9beKyMdhW/JgpbCr5SveIJP1u/k6r8scm+ruixBYqcOdDsvlczN2ynJK+LM341g6LXjapSjlMJhOBjddQhXnDmiRtNlfR3O/IFjB3+k34iaK4PXpTR7P8c++Audb38Dzdz8U7Wv/+5rDv32Gz/t/Y6C4N/456xvmv2aQvij85acx7W9r+WPA/4IwC/HfuGulXcRZYli5tCZ5JTmsL9wP/sL9rOvcB+ZhZnYlXPKhDBzGGld05hzzhxJbvyMLGgpWq3gsGisFbY694cFBTMs4TTWbfuS3NxcevTowdIn59OpU6caxxqGwbtbVnPbsn8wodcYLj3jrAbHo2l6vYeYK6XIWvlv7PvX0/GWBc2W0BTl57F6+ZeUl5cDitDwCC659nrWLl6KvUCGjYu2KyE0gWNlxwD44fAP3PfNffSM6ckLY14gNiS2xvF2w86h4kPsK9hHRk4Gr259lbEpYxnVeVRLhy68RJIa4Ve0sBhwVIDDBnUsSFfbjLu1JTW6rjNpwGiu7TeKWR++y9Ytq0mKCEPTNDQ0FIqI4Aj6pAygd8qZtdbmGI4KNN0Zx7FdP0HhYcDZIqVwDtk2Co9gO/gz2MsJ6zuWDrctrPfrzf15H9ajhSf67WhVboDNsHPMXIyu6zgcdg7s3Y3STIwZfykxCQn1vk5LszkMMo+XUlBmo8zmIMxiJjo0iM6xoQSZZCp70TxCTCFUGBV8l/kd07+ZzoiOI3j6vKcJq7YorYtZN9M1qitdo7pyXufzyDiawfObnmdkp5Gy5EIrJUmN8C8hMc77snyIqH1RuobOuKvrOimlZ3LnjZM8tiulKCzM4+cdm1j4y9ckRrZn9vS5rFmzhsjISOcxhgMqk538//6T6AFjAWfOoaNA0zAl9STxvOvRgxo2d1Nx9jGyv99G/IjulQFxojtRZdZ0ZNdRKiINotpHY9GDGfv7awiPiGjQdVqCYSjW7j3Gqm05/LAnl905xdhrWe/CYtLpmRjByNMSuKB3IkNT4tB1qeoX3mExWdiUvYkv933JqM6jeHr00wTp9asx1TSNaYOmceOXN/Lf/f9lXLeazdrC/0lSI/xLaIzzvjy/zqSmMcymmh+cmqYRHR3HuUPTOJc09u7byeRHrkEzeX4Yu4Z0W8KjiB06AZPFO008R3/dTfshvUlI7Y5hGBQXF6NrunOpAwUYCkteMR27tKdj7/qtG9XSHeTKKhz858f9vLn2Nw7mlZEUFcKo0xOYNCyZHokRxIVbCDGbKLM5OF5Swe6cYn4+WMBHmw+xYPVeuiWEc+OIrlw7NJmQIFm3RzTNJd0vYfGOxQxNGsrcUXPrndC4DEwcyKjOo3gh4wXSuqZh1uUjsrWRd0z4l6o1NV5Un35/3budzn3dZ1H6ZgkPXvcYPXr0YMJlo/j2mzUUFD/NjVdN5NZ3H/QMNwdy4y6p+5rqRKKhuf/nZC+vIHmKcyLLPenbyPxlP1GxUSitcr0p3XmfkJxYr9eoaLnRT0opPth0iH8s305eaQWXDujIc9d0ZVByzEk7WZ7T09lkZhiK9P3HeXvdAeZ8vo1/r9nHrIt7c0n/ji30CkQguvL0K7ny9CubVMblPS7n/u/uJ9+aT0Ko/zbxitpJUiP8S9WamkrenHG3Pi5JnciyNUsBKCws5p1X/4/E7lfTo0cPbv/1V4/+O+WLn6bdNb9r8DVSU1NZs2YNptDKb5KGotfwM+nUJ8UbL6FZ5RZbmfnBz6zclsMl/TvwwNjeJMfX3mehLrquMax7PMO6xzMt7TTmfrmdqe9s5sutWfxtQj+iw5p/1JgQtTladhSLbiEuJM7XoYhGkKRG+Jfwdhh6EMbRXeintcxMvNUld+nOwfz9FJcV0bN3Ip03ryd4Xynd4iLY8e8nSOjdzXmgAi2xu8e5BVnH+eV/GdjtdneNhSU4mGETPEdTVJ17B7y0NIRq/pqaHVlF3PxGOuU2BwtvHMKFfdqf+qRT6NEugoU3DuHTnw7z0MdbmfjS97w6+Sy6JYR7IWIhGuZQ8SE6RnSUjsKtlCQ1wr+YgzmzfRhbt2+j/9kNP33r1mzWbz0xTbqGhqZBbpH1JGfVdPG5VxAROoOLx/2RqNRUZ2hPLUE/7yqCR4+u87xd63+l19AziU8+8WG/ZsmKGsdVnXsnJSWF8eeP48fN6zlekMctt9zCQw891KB4wdXM1Xy9an7KzOf6f6+jU2wo7/1xBJ1ivDt8/NIBHenXKZqbF6VzxUvfs/j2EfRKivTqNYQ4lUNFh+gUUXM0pWgdJKkRfqdrhwQ27DtG/0acu/anLKZc3c/Zl0UZlcOuabERNmFR4ThsJx+NVZvC4iKWvfsRwe3C6dGjB1OmTKl1mLqvbDtSyI2vree09hG8ecswIoKb509HSkI4H955NtctXMekf//Ie3eMoHs7/xvtJQLXweKDpLZL9XUYopGkfk34HeccMo08VwOzWcccpBNkMWOxmAkOMRNkaZmRNYbDgW5u+LUuSbsI8Jx7x1/klVRw25sb6BQTyhs3D222hMYlJszCf24ZSnRoELe9uYGi8ronYxTCm5RSHCo+RKdI//lCIRpGamqE/9FoQlrTNNU7JZcXlbHu4+/QdJ35jz2HXqqR8dU659BrXau8OR/rus6RzCN07NXVo8ySkhIOZOx2H6dV1hpl7zlMRWwpht2BqnC4j6/P3Du1xt7I13zSMpVi+pIMSiscLL59OFEhLdOBNz4imAU3DmHCC98z84MtvDhpUItcV7RtW3O3UmIrca/4LVofSWqEf/KTFckO7voNZdHpN2IgDocD5TAwHA4cDgWGgTIUhsNAKYVhdxARG0VMx3iPMgaNHkrR8UJwGBiGwjAMAPKPHMNWUI7D7kAzm0hM6eCFiL37g1u68SDf7TzK61POonNsw0Y4NVWPdhE8eWU/pr6zmUu2HOGift74+QhRu+ySbKZ/M53+Cf1lmYRWTJIa4Yc0VCPH8Xh7edYQSwjxsXGExTa+X0di944kdq85/0qvkf2IiYkhKMRCrxF9CQq1NCVUoH7z8dRXfmkFcz77lSsHdeb8XvWbK8fbxvfrwKdnHubhT35h1OntCG/mpi/RNpXaSrnn63vQdZ3nLniOYFOwr0MSjSR9aoTfqZyzrlEchRXeDIXmqjJSShETEwM4m7lSK0dYgXPundEnGWHVUuZ/txe7oZh1cW+fxaBpGg9f0ofCMhtv/LDfZ3GIwLb64Gq2Hd/GfYPukwn3WjlJaoTf0bTG96gxRze9tsOD8m7tR7NSoLyUhOWVVPDGD/u4+ZxuJET49ltr59gwrhuWzCvf7aG0ouF9jYQ4lQuSL6B3XG9e/ullSm2lvg5HNIEkNcLvaJr3m5Eay1tJQkvwZqTvbzyIYcDkc1K8WGrj3XpuN4qsdj7JOOzrUEQAspgs/H3U38kqyeLpDU/7OhzRBJLUCL/TlOanZkmGWk1VzYnFN5tCKcW76w9wUb8kn9fSuHSODWNM70TeXX/A16GIANU9ujt/OutPLN25lFUHVvk6HNFIktQIv3OyBRFbXOupqAFNoamm/+x25RSzN7eECan+NVfHZamd+PlgAYfyy3wdighQfzj9D5zf5Xwe++ExckpzfB2OaAQZSiAazPHTl9h+WIlmci094Pzkr9kTRtXyuNq9cp4JGko57+15uRTaBrNxzW9gOFd0VoZCKdc9KEOBqnxc+VwpBYdLOLhkA8dVNpp2Yh4ZNK3yuX7i5tqv6ehBJizhYQRHhhMcFY4lMpygiFBc0bUGzqaypn9PWfFrNuEWEyN6xJ/64BY0ulc7gkwaK3/N5qazU3wdjghAmqYx++zZ/H7Z75n29TQW/G4BkRZZqqM1kaRGNJh2dDulB8OI6FIIwZWLDnrUEDgfq2rPq6cHQx97k1UPXkNkmMU5iFtTgCKqQydGxHSB+DDnpHYmDd2dlIBu0tF1DV0HNK3ysfM24OzOHFq6hm4Th6IczvJU5XwyyjBQDuVcPsEwMByGMzEyFI4KGxUlpZTm5mEtKaWitBR7uZXC3N10CN/F/t+Sq0Suan09J/bVsr167ZOq1gO5RrtZtXJ0E2g6mm4CzQS6jqabQTehBYViCg7jjDwb+7ywCF/6/uMMSYkjJKhlZmGur6iQIPp3jiF9/3FJakSziQ2J5YUxL3DLf2/hzpV38sqFrxAeJIurthaS1IgG04dPIui7PxHUZwjaqHsaXc5PN9fdIa9no0uFw8E6kR3a1diemprKmjVriIys/zev7PQvsZf1odOo3zchosZd28WZlDkwHDaUw44yHJVJmQ1l2LGXFeOwFmP71UqyPbdJcSqlyMjMZ7KfJg0Du8Tw5dYsX4chAtwZ8Wew4MIF3Pbf27hr5V28nPYyYUEtO/mkaBzpUyMaLiKRsDNjKfvfJjAcpz6+DpqmkZ+fD0BKSgqPPPIII0aMoFu3bsyZM8dLwZ6QkZHRqKTC19fWdB3dHIQ5OIygsCgsEbEER8UTGptEWHxnojr3JrbHEI6GGiitaZ2AcosryC+10TspqknlNJczOkRxKL+MsorG/94JUR99E/oy/8L57MjbwZSvppBXnufrkEQ9SFIjGsV07g04ShXs+NJrZebn57N27VrS09N56qmnOHToUKPKqaufcWOSKF03o4ymz43SEgmchkI1sZN1Zp5zjo4ucaHeCMnrusQ5vy0fzJO5RETzG9BuAIvGLSKrJIu7Vt5FcUWxr0MSpyBJjWicToMxx+nYNq/2WpHXXXcd0PSVqus7rLs+SZRuDsKweXuWYu8lcFUp1fROzTmFzs7fSVEhTY6nObjiyimynuJIIbyjV1wvXk57mf2F+7n5q5vJLWtaE69oXpLUiEYLirJjL/Heqs0hISc+SBu7UjVQ76ymPkmUZg7CcHi/qcNbCVxVuqLRa2a5lNmcP3N/XWMp1OLsvJx5XGpqRMvpE9+HN8a9wdGyo9z/7f1YHZJU+ytJakTjafjP1L9V1bMJpj5JlKbroLyf1HgtgasiSDmo0JuW1FhtzhXELSb//tOwarvMISJaVq+4Xjxz3jNsyd3Cbf+9jQqH92twRdP5918u4ed0WtfsdI3RWmapAV0ZGE38J+0axm21G94IyetUZRJ96YCaq54L0dwGtR/Ea2NfY2vuVv669q/u30fhP/yzjlm0Ejoajf/wq/oHYf/+/R77NmzY0Phy7Q5yNu9EM1VOuqfrRHVJbHR5rYWmmr5SVVhl806x1e5u6vEnpZWjnhIivLxwqRD1lJqYyl/P+St/XvNnQswh/GXYX/xrFvQ2TpIa0WjKTyv6Ol44gKL92ZWzDBvgMMhe9QuFB3OIjIkBvJtE1UdzJXDVNXXtp6RoZ7PYkYIy2kX6x7pPVR0ucC6R4K8dmUXbcEn3S6hwVPDoD49SbCvmsRGPEWKW30l/IEmNaDxNgybU1DSXmO4dienu2TxhO8/K7v98wxm3j/NRVM1PQ6GamGd2iXUOmT5wvJT+nWOaHpSXZR4vRdOgU6x/DjkXbccVp11BmDmMh79/mOySbF4f97qvQxJIUiOaQvlnn5pf53+JVtk3RNkcxPTvQsez+2KKCKboYA6RnRvWFKX8L2+rnRdGP8WEBdEuMphfDxdySX//67fyy+FCUuLDCTb7X9OYaFtKbCV8se8Lyh3lRFgifB2OqCRJjWg8TcMfkxotyMQZt/zO/Xzbwq/oeHZfok7rQMHerAYlNZpuwh9fY+3qWHeqATRNY2CXGDYd8M/ZUzcfyGdgcoyvwxBtXF55HnetvIutx7YyKHEQT4x8wtchiUr+2SlCtBKmJnUUbjbVRyRUDnPWTBrK3rDh2ZqutZoRDialMLwwWmtY93g2Hcin2Nr0YebedKzYyi+HCxjWLc7XoYg2LKski8nLJ3O45DDvXfIeiy5aRJTFP5cVaYskqRGN5mzq8MMP/OojEQxnjMExERRuO9KwonRTq2l/MjTvDEC/8Iz2VNgNVu886oXSvGfVthwUMOaM9r4ORbRR+wv2c+OXN1JuL+fNi97kjPgzfB2SqEaan0QT6Piio/DB736iYOshgmJC0YPNaLoGaKA7J8tz5Jd7HG8Ks/Dr/C8xhVs4/eYxDbuYpqOM1pHUKFXveQdPKjk+jDM7RvHhpoNc3K9D0wv0kg83H2RoShwJEf43KksEvl+P/cqdK+8kJjiGVy58haTwJF+HJGrRpKRm7ty5zJo1i2nTpjFv3jwAFixYwDvvvMOmTZsoKioiLy+PmMphtCfz4osv8tRTT5GVlcWAAQP417/+xdChQz2OWbt2LX/5y19Yt24dJpOJ1NRUvvrqK0JDZSSEL2hmKN2jYXvkBkAHXXfeaxpoepUboCk0rfJTV3M266BpoCvnB7H7XnPO4KuUs4JEAQYoQwN0lDJx+HAyYVFfUnIoBKUql2nQdBQaGjomk52dc/7lvJSmoSuNYA20fDj4/FNomoZJ17GEhWIJDSMoLAJLeBRBYVFoIZFgiQCTBSpKUAd2wMFM+K6k8nXoVL6AyptW97YajytvQWEQGgMhMRAS7Xxsiaz8+eHMThwVYLdWZilazbJMtS1PoQCdCmspO9Z9RcHBvTis5dhtVgxbBY4KK0ZFBQ5bBcpmQ7c70NEYcudDJHY+3aOk64Yl8/DHWzmYV0rn2DDstgqOZ+2jIOcgRblHKC84XvP3QdOwhEcREhVDSGQsYdHxhEfGEx4dj8nctOU0ducU8ePe4zx3TeopjzUMA4e9giBLCEopbKXFOGxWFBAaHo0W5L2lPUTbsCFrA/d8fQ8pUSm8lPYSsSGxvg5J1EFTjewwkJ6ezlVXXUVUVBTnn3++O6mZN28e5eXOb8qzZs2qV1KzZMkSbrzxRubPn8+wYcOYN28eS5cuZceOHSQmOjt1rl27lnHjxjFr1iwuvfRSzGYzP/30E5dffjnBwaf+5lZYWEh0dDQFBQVERUn7p1fk7oJ9q53NM4bDmYx43BsoR+VzhwGG4az1MBQYDudjhwJDoQzXPe4PcM2kgV55r+mVSZEDAwdKOVBKoQwDReW5VJZD5XalUMrVxca5z3WMw26noryMitJSbNYyKsqt2CoqEwm78wMQ3YzSLfSOySXMXJlhKWf5Jx7DiYsoz2Pc2+pDA3Ow8+dm2E59uG52JkeWSAiJgtAYPtmzg4jtJuJ3BhFcSxEODewmMEwaDpOG3aQRVewg8/rRjPvLywAUFxwj89cfObRlI2u/W0/P0nyS8oqJP2olqAmrRVjNYA3WsQXrWINNGGZnsqY0UJUJrtKc77eqTHxdCbHSNYorHFgNRVxEcGVypzmTwMpzsDsIOl5EeH450YUGJgWF4RohVoWlStcghwZ5sUGUx4TgiI5Ai4mG6AgcocGVkzXqaLrzhm4CXUd3P9fRTCY0rfKxbkIzmdArj0sePIqOPQew4eOF2K2lRCYlM/B3kxr/Q2sEW4Xzb69uMqNpzthF0034eAKRlkjmXzif8KBwX4fT5jTk87tRSU1xcTGDBg3ipZdeYs6cOaSmprqTGpdvv/2W888/v15JzbBhwzjrrLN44YUXAOc3rS5dunDPPfcwc+ZMAIYPH86FF17I448/3tBwAUlqRAMYBhh2MHtp1lpX0qMMZ4JXUQJleVCeD+UFUJbvfGwtAj0IgkLAHHri+lXPRzljsxZB6XEozoaSXCg9xvaVeyk+YCH34nPpeE4anXsNwRIajiU4jCBLCJqp5jDoFWOHEFRmoywhnKjDhcTln8hc8iJ0DsaEENSjI+Gn9SAiuTvh8UlEJnYkIqZd5ciwKj82u42y4nzKCvMoK8qjorgAa1EB9uIibCVFOEpKUKWlaGXlaHZnknvitanKn7uqtk1htzs4XlxOlMVMqFn32K+5jtd1jPhoTImJBLVvjwoyYz1yGHNUNKbYGPTK2pmyvFyMAwdReflo+cUEFZURVuIguMJAU6Ap0A3lfqwp50Khrtup7B2URPdNWQDYdejz889NrqWqr92bv6Xk+juxVEk+DcDQwVzZgmqr9iugwJlYVt4MXTvxuDKhdD4/cW/oOJNQvXJ7lUTU9didqFbea4ai05//wpkjL2+215+elc7K31ZiKOcXHUMZNR8rhUGVx/XYb2CwOXszN515E/cOurfZ4hd1a8jnd6Oan+6++27Gjx9PWloac+bMaVSQLhUVFWzcuJFZs2a5t+m6TlpaGmvXrgUgJyeHdevWMWnSJM4++2z27NlD7969eeKJJxg5cmSTri9EDboOuhen4XfVLKADZmeNTJj3R/CE/Xg7EYOCGfKXf9X7HMeoswj+8nuU2UT+uX2x9jiNdr1T6dJ3OClRScx4+lv6dIzi1ZuG+GQqeMNQXLPwR7ILy1lx33lYzL6teTAcDhwOG8ph4FB2HDYbSjlY/fg9dP/8Z7pvyqIkRKM4wkR5h1j6tVBCA1Bw5DfCHPDb9aOwxCU4aysNZ/LYaf5nABw47zSCevSoPMOZSCpXkugwKmtdqyaZlTWslftUZSKqHA4014zdlTWvzppWA60yOXXtC8otoMveInJ2/wLNmNS8u/1d/nfofyRHJqNrurPpGf3EY013NlBreo39VbeZMTtr5yrP0dG5MOVCxnRtYH884RMNTmoWL17Mpk2bSE9P90oAubm5OBwO2rf3HNHQvn17tm/fDsDevXsBeOyxx3j66adJTU3lzTffZMyYMWzdupXTTjutRrlWqxWr9cTy8IWFhV6JVwi/pRo+T824v7wMf6l7/5wJfbn1zQ18uOkQVw7u3LT4GuGtdb+xft9x3rltmM8TGgDdZEKvpcZr/DNL4Bnn401rP6b9lFmU3HNVC0fndMYVN9O1zzCPbZ/9/DOmvCIG/+lvdOjWt0Xj+fHdeTD7FbqfN75Zr6NrOgPaDWDh7xY263WEf2tQUpOZmcm0adNYsWIFISEtt86FUTn65I477mDKlCkADBw4kFWrVvHaa6/x5JNP1jjnySefZPbs2S0WoxA+563hT1Wk9WnPFYM68dDHWzmzUxS9k1qu6XbzgTzmfLaNG0d05eweCS123aba885CUsJ1Bk241TcB1NKj4JLXvvJBIE55O3/BHKLRO6V/s15H13SMVjL9gmg+Dfrqs3HjRnJychg0aBBmsxmz2cx3333H888/j9lsxuFoeE/ChIQETCYT2dnZHtuzs7NJSnIOmevQwTmstE+fPh7HnHHGGRw4cKDWcmfNmkVBQYH7lpmZ2eDYhGhVmiGpAXhiQj9SEsK5ddEGsgrKT32CFxw4Vsod/9lI305RPDS+z6lP8BNFJfl0+X4vRecPwhTcwgsc+ulC0dYD+ylsF9bszZeS1AhoYFIzZswYtmzZQkZGhvs2ZMgQJk2aREZGBqZaqmVPxWKxMHjwYFatWuXeZhgGq1atYsSIEQCkpKTQsWNHduzY4XHuzp076dq1a63lBgcHExUV5XETIrAp9+zJ3hRqMfHvm4agFFxX2b+lOWUeL+XahT8SHmxm/g2D/aLZqb72rl9BdCl0nOCbpid/ZD5WhD28+ecWMmkmSWpEw5KayMhI+vbt63ELDw8nPj6evn2d7bRZWVlkZGSwe/duAHcSdPz4iXktxowZ4x7pBDBjxgwWLlzIokWL2LZtG3feeSclJSXupiZN0/jTn/7E888/z/vvv8/u3bt5+OGH2b59O7fcckuTfwhCBAKlVLN9G+4UE8o7tw2jzOZgwovf88vhgma5zsbf8pj40veYdI23bx1GYmQL13Y0kb1ySHVIdLwPrl753vvZJN/ms1LpuOM41rLiZr2Oruk4VBPmHRABweszCs+fP9+jL8uoUaMAeP3115k8eTIAe/bsITc3133M1VdfzdGjR3nkkUfIysoiNTWV5cuXe3Qenj59OuXl5dx3330cP36cAQMGsGLFCnq4e/IL0cYpaM42iK7x4Xx89zncumgDV778AzPH9ebGESnoXqgdchiKBav38s8VOxnQJZr51w8mvhXOHOwwnB+qtXUmbrs0KoIgKDisWa8iNTUCvJDUfPvttx7PH3vsMR577LGTnrN///4a26ZOncrUqVNPet7MmTPd89YIIaoxjGbpU1NV+6gQ3rtjBHO/3MZjn/7Kpz8fYdZFvRmS0vgh6j/szmXu8u1sOVTA7ed2Z8bvTifY3DqTAlWZ1Jh0H6xA43rr/WwBVvvhwxTEBTf7RICapklSI2TtJyECRjN1FK4u1GJi9uV9Gds3iSc+38bv569lWLc4Jg3vStoZiYRZTv1npdhq57+/ZPH2ugNs/C2P1C4xvP/HEQzu2rpX4HZ9qOpa6+kH1NxM2ccoaxfZ/NeRmhqBJDVCBI4WSmpczu6RwKdTR/Ll1iwWrd3Pve9uxmLSGdotjjM7RdGzXQSxYRZCLSZKKxzklVSw+2gxWw4WsOG349gcipE9E1hww2Au7NPeJ5P7eV1lLYnm06FI/lVTYyoux96pXbNfR/rUCJCkRoiAoVCVK5a3HF3XGN+/A+P7d2BfbgnfbM/h+925fPbTEQ7ll9U4vktcKL2Tonj4kj6c3yuRLnHN28/CV5Qvcho/TQptQRpmW/PXoEhNjQBJaoQIHM3cUfhUuiWE021kN24e2Q2AcpuDonI7ZRUOQi0mokLNrbavTL25+rP4MsHwtz41Jgi2N3+yIX1qBEhSI0TgaOHmp1MJCTIREhTgSUw1miufkJoaN5NdYbTA74HU1Aho4Dw1Qgg/5mdJTVvmX3UlvmW2GRhBzf/9WfrUCJCkRojA0QJDusUpKF9W1bhi8N2la2O2G6h6jIhrKqmpESDNT0IEDIXy2/V/2ozKhKLg6EGCQsOc7wl49HNRqua2KjtrLTY4PJKwiDiCgkNb3Sgxk11hNTX/92fpUyNAkhohAodCamp8LCg03Plgyv3knvzQRnFoUBEEFRYdu0XHYTFjhFhwWMxEHylshis2nTUqFHKPn/rAJjJpJml+EpLUCBEwlEKTSd98asCYq9n09zLs5c7h7B4pZuV745F31pqEem5TysBWXoq9tAR7WQmO0lKMsjKMsjIcZaU4ykrRrBVYQ2LJsQRxwWn9vPqamsreJZHwXw80+3VklW4BktQIETiko7DPmYMsDL38dl+H4Ve08DDMFc1fgyJ9agRIR2EhAockNcIPqeISKkKb//uz9KkRIEmNEAFDKUM6Cgu/o+UXYYsIafbrSJ8aAZLUCBE4pKOw8EMhRwuxt2/+hUqlT40ASWqECBxKtbrhviLwhRZWoMXHNvt1pE+NAOkoLETgUAppfxL+piLEhCosojAvG8NhRxkODIcDw3A4HxsOlMOBMgyMyn3Ktc/hQCkD5TBOHGtUHuuwV5bjLLPsyAYS8+2+frnCxySpESJQKAW6VL4K/2KNDKbHqp0cWjXaq+XqeDY1jAQGhWgwzauXEa2MJDVCBAoZ/ST8UM8nn+HQpv+BrqHpOppuQtN10HR004nHmq6jmSr3azpa5T5NN6HrpsrzTc5z3OeaMekmNLMZVqwh7NV3fP1yhY9JUiNEwJBlEoT/6dH/XHr0P7fZr5P36xGyDOlT09ZJXbUQAUIZ0lFYtF2aSQelTqytJdokSWqECBTSUVi0Za4lQqS2pk2TpEaIQCF9akRb5uokLzU1bZokNUIECklqRBum6ZW/+1JT06ZJUiNEoFAKdElqRBtVWVOjJKlp0ySpESJAKKSjsGjDdOlTIySpESJwyNpPog3T3DU10qemLZOkRohAYRjI6CfRZrlGP8n6T22aJDVCBArpKCzaMld/MofDt3EIn5KkRohAIUmNaMM0kwlAJt9r4ySpESJAKFkmQbRlMvmeQJIaIQKHOtFZUog2p7L5SUnzU5smfwGFCBSyTIJowzSZUVggSY0QgcMwpE+NaLt0Z58aaX5q2ySpESJQSEdh0YbJMgkCJKkRImBIR2HRpskyCYImJjVz585F0zSmT5/u3rZgwQJGjx5NVFQUmqaRn59fr7JefPFFUlJSCAkJYdiwYaxfv77W45RSXHTRRWiaxscff9yU8IUILDKjsGjLZPSToAlJTXp6Oq+88gr9+/f32F5aWsq4ceP485//XO+ylixZwowZM3j00UfZtGkTAwYMYOzYseTk5NQ4dt68ebK+jRC1UUpGP4k2SzNJTY1oZFJTXFzMpEmTWLhwIbGxsR77pk+fzsyZMxk+fHi9y3v22We57bbbmDJlCn369GH+/PmEhYXx2muveRyXkZHBM888U2O7EAIZ/STaNhn9JGhkUnP33Xczfvx40tLSmhxARUUFGzdu9ChL13XS0tJYu3ate1tpaSnXXXcdL774IklJSU2+rhABRzoKi7ZMk2USBJgbesLixYvZtGkT6enpXgkgNzcXh8NB+/btPba3b9+e7du3u5/fd999nH322Vx++eX1KtdqtWK1Wt3PCwsLvRKvEH5LhnSLNkxW6RbQwKQmMzOTadOmsWLFCkJCQporphqWLVvG119/zebNm+t9zpNPPsns2bObMSoh/IsCaX0SbZdrnhpZpbtNa1Dz08aNG8nJyWHQoEGYzWbMZjPfffcdzz//PGazGUcjqv0SEhIwmUxkZ2d7bM/OznY3M3399dfs2bOHmJgY93UBrrzySkaPHl1rubNmzaKgoMB9y8zMbHBsQrQqSkknetF2yTw1ggbW1IwZM4YtW7Z4bJsyZQq9e/fmwQcfxFS5SmpDWCwWBg8ezKpVq5gwYQIAhmGwatUqpk6dCsDMmTO59dZbPc7r168f//znP7n00ktrLTc4OJjg4OAGxyNEqyV9akQb5m5+ckhS05Y1KKmJjIykb9++HtvCw8OJj493b8/KyiIrK4vdu3cDsGXLFiIjI0lOTiYuLg5wJkcTJ050Jy0zZszgpptuYsiQIQwdOpR58+ZRUlLClClTAEhKSqq1c3BycjLdunVr4EsWIkApdWKuDiHaGvfoJ0lq2rIGdxQ+lfnz53v0ZRk1ahQAr7/+OpMnTwZgz5495Obmuo+5+uqrOXr0KI888ghZWVmkpqayfPnyGp2HhRAnITU1og1zz9EkzU9tmqZU2xjUX1hYSHR0NAUFBURFRfk6HCG8bsegwSTcew/xlV8ehGhLrHv2sHf8JXR9523CBg3ydTjCixry+S111UIECCUdhUVbJsskCCSpESJwSPOTaMNcq3TLMgltm9f71AghfESWSRABQilF0ZdfYt29B/uxY/WqfTFKiisftIkeFaIOktQIESikpkYECNvBgxyacT+muDiCkpKgntOFhA0ZgqVbSvMGJ/yaJDVCBAqlTkxAJkQrZpSVAdDlpRcJTU31bTCiVZE+NUIECOcyCZLUiNZP2WzOB0FBvg1EtDqS1AgRKGT0kwgUlUmNJkmNaCBJaoQIFLJKtwgQrpoa3WLxcSSitZGkRohAIaOfRIAwKioAqakRDSdJjRCBQkY/iQAhfWpEY0lSI0QgkZxGBAAlfWpEI0lSI0QAcC3h5l7UT4hWzCgpAUAPD/dxJKK1kb+AQgQC17q00vwkAoBRWIQWEiIdhUWDSVIjRCBwTyMvSY1o/RxFhZgiI30dhmiFJKkRIhBITY0IIEZhEbokNaIRJKkRIhBIUiMCiB4e5u5XI0RDSFIjRABwr0ssOY0IAOYOHbDn5JwY2i1EPUlSI0QgkNFPIoAEJXUApbBl5/g6FNHKyF9AIQKBND+JAGKKjgLAKCr0cSSitZGkRohA4EpqpP1JBACjtBQAPSLCx5GI1kaSGiECgWtIt9TUiABgFBcDktSIhjP7OgAhRNNJRY0IJIbVCsDuC8agBwc7J+ILDkarfGyKiqLDE08Q1D7Rx5EKfyNJjRABobKjsNTUiAAQcd5oOjwxB6O4GMNagSovx7CWo8qtOPLyKPziC6y7dklSI2qQpEaIQCAdhUUAMUWEE3PllbXusx06ROEXX0itpKiV9KkRIhC4kxr5Jy0Cm3vxVkngRS3kL6AQgUBqakQboSoqANBCQnwcifBHktQIEQjcSY1vwxCiuRllZQDoktSIWkhSI0QAUFJTI9oIVV4OgBYS6uNIhD+SpEaIQCD9DEQbYZQ5kxo9VGpqRE0y+kmIQCA1NaKVKt++nX0TJqKFhmKOjUWdWJ71xEqt6sQ2V02NHio1NaImSWqECASS1IhWyjVrcFCHDkT+7kKP3+ETNY+aawMA5nbtMMXEtGCUorWQpEaIQCBJjWilzO3aAZDwxzuIvuwyH0cjWjvpUyNEAJCOwqK10iwW0DR3XxkhmkJqaoQIBNJRWLQyFQcPYt21C3NsLCiFKi/zdUgiAEhSI0QgkJoa0UoopTj2yivkvvgSymY7scMkH0ei6ZrU/DR37lw0TWP69OnubQsWLGD06NFERUWhaRr5+fn1KuvFF18kJSWFkJAQhg0bxvr16937jh8/zj333EOvXr0IDQ0lOTmZe++9l4KCgqaEL0TgkKRGtBJ577zD0XnPETd5Mj2/+Zpun3xMygfvE3vN1b4OTQSARic16enpvPLKK/Tv399je2lpKePGjePPf/5zvctasmQJM2bM4NFHH2XTpk0MGDCAsWPHkpOTA8Dhw4c5fPgwTz/9NFu3buWNN95g+fLl3HLLLY0NX4jA4h7yKkmN8F+27Gxynn6G2OuuJfH+GQR16EBIr16EnnkmmllqakTTNSqpKS4uZtKkSSxcuJDY2FiPfdOnT2fmzJkMHz683uU9++yz3HbbbUyZMoU+ffowf/58wsLCeO211wDo27cvH3zwAZdeeik9evTgggsu4IknnuDTTz/Fbrc35iUIEVikpka0Atlz56KHhNDuvvt8HYoIUI1Kau6++27Gjx9PWlpakwOoqKhg48aNHmXpuk5aWhpr166t87yCggKioqIwS3YvRJVFuiWpEf6p8IsvKPpyOe3//GdMkZG+DkcEqAZnBIsXL2bTpk2kp6d7JYDc3FwcDgft27f32N6+fXu2b99e5zmPP/44t99+e53lWq1WrFar+3lhYaFX4hXCP0lNjfBftpwcsmb/lciLxhF1yXhfhyMCWINqajIzM5k2bRpvv/02IT5aIbWwsJDx48fTp08fHnvssTqPe/LJJ4mOjnbfunTp0nJBCtHSDMN5L0mN8DNKKY48/DBYgkh65BGZdkA0qwYlNRs3biQnJ4dBgwZhNpsxm8189913PP/885jNZhwOR4MDSEhIwGQykZ2d7bE9OzubpKQkj21FRUWMGzeOyMhIPvroI4KCguosd9asWRQUFLhvmZmZDY5NiFZDOgoLP5W/5D1KvltNh8cfd85JI0QzalBSM2bMGLZs2UJGRob7NmTIECZNmkRGRgYmk6nBAVgsFgYPHsyqVavc2wzDYNWqVYwYMcK9rbCwkN/97ndYLBaWLVt2ypqi4OBgoqKiPG5CBCzpKCz8UMVvv5H9978Tc9VVRI4e7etwRBvQoD41kZGR9O3b12NbeHg48fHx7u1ZWVlkZWWxe/duALZs2UJkZCTJycnExcUBzuRo4sSJTJ06FYAZM2Zw0003MWTIEIYOHcq8efMoKSlhypQpwImEprS0lLfeeovCwkJ3H5l27do1KpkSIpCcWCbBt3EI4aLsdg4/OBNzu3a0f/ABX4cj2givDx2aP38+s2fPdj8fNWoUAK+//jqTJ08GYM+ePeTm5rqPufrqqzl69CiPPPIIWVlZpKamsnz5cnfn4U2bNrFu3ToAevbs6XG9ffv2kZKS4u2XIUTr4q6okaxG+Idj/36Vsp9/putbb6GHh/s6HNFGaMr9FS+wFRYWEh0d7R4KLkQgse7dy96Lx9P17bcIGzzY1+GINs5+9Ci7LxhD3OTJJN4/w9fhiFauIZ/fskq3EIFA+tQIP5K3dCkEBRF/262+DkW0MZLUCBEIXEO6pVON8DFlGBR+/gWR55+PSWrFRQuTpEaIACAdhYW/KPvpJyr27CHmD3/wdSiiDZKkRohAIB2FhZ8oXbcePTycsCHSt0u0PElqhAgI0qdG+IfS9esIGzJEVt0WPiG/dUIEAlfzky7fU4TvqIoKSjdtJv7227Dn5mKUlmKUlWGUlFY+LkWVlqJHRhF5wfm+DlcEIElqhAgEskyC8APWfftQ5eXkPv8vcp//10mPPX1DOqaICK9d2ygro+K33wjp3dtrZYrWR5IaIQKAkgUthR8I7t6dTs8+gzIUelgYelho5X0YemgoWlgYJWvWcPiBB712TevefRxftIjCzz/HKC6m57ffEFRt3UDRdkhSI0QgkIoa4Qe0oCCiLr745AfpzmVtNC80lZZu3EjmHX9EDwsjfORIipYvxygtbXK5ovWSBnghAkFl85OMfhJ+z2F33jexI7FRXs7hBx4k+PTT6f7FF8TfcgsAqry8qRGKVkxqaoQICDL6SbQOyuFsKtWauBBx4WefYTt8mC4LF2KKCEePcK4v5SgubnKMovWSmhohAoEskyBaCeWqqWli81PhF18SNmwYwd27Abg7HRslJU0qV7RuktQIEQjcSY38kxZ+zuEAk6lJTaVGaSkl6eno4eFYd+8GcK8EbhRLUtOWSfOTEIFAlkkQrYRyOJrc9FSWkQE2G8WrVuHIzyfl7bfQQkNB1zFKpPmpLZOkRogAoAzpKCxaicqamqYoXLECLTgYDIOwgamA83dfDwnBKJOOwm2ZJDVCBATpUyNaB2Vvek1Nxf79RJx3Hp2em+eRyCubDc0S1NQQRSsmSY0QgUA6CovWwnCgrFay5/4dLSjIebNU3gdZ3I8xmSj++hvibriesLPOcp+u7HYqdu8heuJEz4TGMFA2G3pwsC9elfATktQIEQgkqRGtREi//lh69qR4zRpURQXKZqtxw253H2+UlJBcJanJ+uvj2PPyiDh/tEe5qqICwNksJdosSWqECASy9pNoJcKHDaX7Rx+e9BhlGDjy89l19jlEX3ape7tRVkb++++TOOM+wgYO9DzHagVAs0hS05bJ+E8hAoByzSisS1IjWj9N1921jq6h2gAVBw6AYRCamlrjHMOV1ARbWiRG4Z8kqREiELgraiSpEYHB3ZwUdKLjr6VLFzCbKd+5s87jpU9N2yZJjRCBQMkq3SKwKJsNAM1youZFDwsjbOBAir/+xr2tLCMD25EjJ5qfJKlp0ySpESIQSEdhEWBURWVSE+Q5RDvq0kso+eEHjr3xBtlPPcX+a65l3xVXnqjZkT41bZp0FBYiEEhSIwKMstVsfgKImTiR4m++JWfu39HDwgBw5OVhVK7OrUufmjZNkhohAoCS0U8iwLhraiyeSYoWFESXl1/CqKjAnpPDnrQLATBKSisPkH8DbZkkNUIEAqmoEQHG1aemtiUVjLIysubMoeCTZQR16kTnF/7lPs4olrWf2jLpUyNEIHDV1OjyT1oEhqCk9mjBwRz+vz9h3bXLvd26Zw/7r7qKgg8+JCw1leRFiwg54wxMUVEAOIqKfBWy8APyF1CIgCBVNSKwBHXsSMp774Ey2Pf7P5C3eDEFn37Kvj9chTIU3T9dRte3/oOlcycAd/8adzOUaJOk+UmIQGDIkG4ReEJ6nU7K0qVk//3vZD02272961v/wRwb63mw/O4LpKZGiIAgHYVFoNJDQujw6KPOfjOVdo04G6OszIdRCX8lSY0QgcA9pNu3YQjRXCLT0uj57YlJ92rrQCyEND8JEQjcXWokqxGBKygpiR4r/ouy2dAtMh+NqEmSGiECgnQUFm2DpUsXX4cg/Jg0PwkRCGRItxBCSFIjRCBQMvpJCCGaltTMnTsXTdOYPn26e9uCBQsYPXo0UVFRaJpGfn5+vcp68cUXSUlJISQkhGHDhrF+/XqP/eXl5dx9993Ex8cTERHBlVdeSXZ2dlPCFyJwuEc/CSFE29XopCY9PZ1XXnmF/v37e2wvLS1l3Lhx/PnPf653WUuWLGHGjBk8+uijbNq0iQEDBjB27FhycnLcx9x33318+umnLF26lO+++47Dhw9zxRVXNDZ8IQKLdBQWQojGJTXFxcVMmjSJhQsXElttAqTp06czc+ZMhg8fXu/ynn32WW677TamTJlCnz59mD9/PmFhYbz22msAFBQU8Oqrr/Lss89ywQUXMHjwYF5//XV++OEHfvzxx8a8BCECi6zSLYQQjUtq7r77bsaPH09aWlqTA6ioqGDjxo0eZem6TlpaGmvXrgVg48aN2Gw2j2N69+5NcnKy+xgh2jZJaoQQosFDuhcvXsymTZtIT0/3SgC5ubk4HA7at2/vsb19+/Zs374dgKysLCwWCzExMTWOycrKqrVcq9WK1Wp1Py8sLPRKvEL4JRn9JIQQDaupyczMZNq0abz99tuEhIQ0V0xe8eSTTxIdHe2+dZG5DUQgk2UShBCiYUnNxo0bycnJYdCgQZjNZsxmM9999x3PP/88ZrMZh8PR4AASEhIwmUw1RjJlZ2eTlJQEQFJSEhUVFTVGUlU9prpZs2ZRUFDgvmVmZjY4NiFaC2U4kxppfRJCtGUNSmrGjBnDli1byMjIcN+GDBnCpEmTyMjIwNSItTgsFguDBw9m1apV7m2GYbBq1SpGjBgBwODBgwkKCvI4ZseOHRw4cMB9THXBwcFERUV53IQIWNJRWAghGtanJjIykr59+3psCw8PJz4+3r09KyuLrKwsdu/eDcCWLVuIjIwkOTmZuLg4wJkcTZw4kalTpwIwY8YMbrrpJoYMGcLQoUOZN28eJSUlTJkyBYDo6GhuueUWZsyYQVxcHFFRUdxzzz2MGDGiQaOshAhcktQIIYTX136aP38+s2fPdj8fNWoUAK+//jqTJ08GYM+ePeTm5rqPufrqqzl69CiPPPIIWVlZpKamsnz5co/Ow//85z/RdZ0rr7wSq9XK2LFjeemll7wdvhCtk9TUCCEEmlJtYyrSwsJCoqOjKSgokKYoEXAKPvmEww/OpNdPGejBwb4OR4gW5ygqYudZQ+k0bx5R48b6OhzhRQ35/Jbxn0IEANd3E5lRWAjRlklSI0QgcI/olqRGCNF2SVIjRCCQVbqFEEKSGiECg3QUFkIISWqECAQy+kkIISSpESIQKElqhBBCkhohAoKMfhJCCElqhAgICqmlEUK0eZLUCBEIlCFJjRCizZOkRohAoJQkNUKINk+SGiECgJKkRgghJKkRIiBIUiOEEJLUCBEQFEhKI4Ro6ySpESIQSE2NEEJIUiNEQFAKdPnnLIRo2+SvoBCBQIZ0CyGEJDVCBAIZ/SSEEJLUCBEYpKOwEEJIUiNEQJCaGiGEkKRGiIAgSY0QQmD2dQBCiKbTzCaM4mIyp06tXKlbcyY5rkRH0yo3NW4fmua5/2T7GnrN+pZb2z7Xfve+U5dbr2vWKLcB13Qnl/Xb51Gux/6qP4OTvflN3H+yhstTln2qS7dA7JXHqPKyUxwr2gJJaoQIAOFnn03EBRegKipQCmfNjVLOnc4Nzs7Ern1UOUYpFN7f574mnDim+rle3ueKQ1WPpUp8jd0nWgdTVKSvQxA+JEmNEAEg+LTT6PLSi74OI+CpuhKe6glR1cdKVW6qa1+1xKm2fbUGc9JIT/YiWnTfyfPBUySLp7pmtZ+dFhREUKdOJy9TBDRJaoQQop40jyaiavtaOBYhRE3SUVgIIYQQAUGSGiGEEEIEBElqhBBCCBEQJKkRQgghRECQpEYIIYQQAUGSGiGEEEIEBElqhBBCCBEQJKkRQgghRECQpEYIIYQQAUGSGiGEEEIEBElqhBBCCBEQJKkRQgghRECQpEYIIYQQAaHNrNKtKpemLyws9HEkQgghhKgv1+e263P8ZNpMUlNUVARAly5dfByJEEIIIRqqqKiI6Ojokx6jqfqkPgHAMAwOHz5MZGQkmqa5txcWFtKlSxcyMzOJioryYYQC5P3wR/Ke+B95T/yPvCfNRylFUVERHTt2RNdP3mumzdTU6LpO586d69wfFRUlv4h+RN4P/yPvif+R98T/yHvSPE5VQ+MiHYWFEEIIERAkqRFCCCFEQGjzSU1wcDCPPvoowcHBvg5FIO+HP5L3xP/Ie+J/5D3xD22mo7AQQgghAlubr6kRQgghRGCQpEYIIYQQAUGSGiGEEEIEBElqhBBCCBEQAiqp2blzJ5dffjkJCQlERUUxcuRIvvnmG49jDhw4wPjx4wkLCyMxMZE//elP2O12n5TbFjTHz+7bb79F07Rab+np6QDs37+/1v0//vhjs77e1sBX7wnAzz//zLnnnktISAhdunThH//4R7O9ztakOf/GfP755wwbNozQ0FBiY2OZMGGCx/7a3rPFixd78+W1Sr58T+TzpAlUADnttNPUxRdfrH766Se1c+dOddddd6mwsDB15MgRpZRSdrtd9e3bV6WlpanNmzerL774QiUkJKhZs2b5pNy2oDl+dlarVR05csTjduutt6pu3bopwzCUUkrt27dPAWrlypUex1VUVLTI6/ZnvnpPCgoKVPv27dWkSZPU1q1b1bvvvqtCQ0PVK6+80iKv258119+Y999/X8XGxqqXX35Z7dixQ/3yyy9qyZIlHscA6vXXX/d478rKyprttbYWvnpP5POkaQImqTl69KgC1OrVq93bCgsLFaBWrFihlFLqiy++ULquq6ysLPcxL7/8soqKilJWq7VFy20LWupnV1FRodq1a6f++te/ure5kprNmzd758UECF++Jy+99JKKjY31KOPBBx9UvXr1aurLatWa6z2x2WyqU6dO6t///vdJrw+ojz76qOkvJID48j2Rz5OmCZjmp/j4eHr16sWbb75JSUkJdrudV155hcTERAYPHgzA2rVr6devH+3bt3efN3bsWAoLC/nll19atNy2oKV+dsuWLePYsWNMmTKlxr7LLruMxMRERo4cybJly7zzwloxX74na9euZdSoUVgsFo9yd+zYQV5enpdeYevTXO/Jpk2bOHToELquM3DgQDp06MBFF13E1q1baxx79913k5CQwNChQ3nttddQbXz6Ml++J/J50jQBs6ClpmmsXLmSCRMmEBkZia7rJCYmsnz5cmJjYwHIysry+EUB3M+zsrJatNy2oKV+dq+++ipjx471WLA0IiKCZ555hnPOOQdd1/nggw+YMGECH3/8MZdddpmXXmHr48v3JCsri27dutVZruv6bU1zvSd79+4F4LHHHuPZZ58lJSWFZ555htGjR7Nz507i4uIA+Otf/8oFF1xAWFgY//3vf7nrrrsoLi7m3nvvba6X7Pd8+Z7I50nT+H1NzcyZM+vsgOi6bd++HaUUd999N4mJiaxZs4b169czYcIELr30Uo4cOdLo6zdXua2Zr9+Tqg4ePMhXX33FLbfc4rE9ISGBGTNmMGzYMM466yzmzp3L9ddfz1NPPeWV6/qb1vCetDW+fk8MwwDgL3/5C1deeSWDBw/m9ddfR9M0li5d6j7u4Ycf5pxzzmHgwIE8+OCDPPDAA/LvxMfviWg8v6+puf/++5k8efJJj+nevTtff/01n332GXl5ee5l31966SVWrFjBokWLmDlzJklJSaxfv97j3OzsbACSkpJqLbu5ym3NfP2eVPX6668THx9fr9qXYcOGsWLFilMe1xq1hvckKSnJXU5jym1tfP2edOjQAYA+ffq4twUHB9O9e3cOHDhQZ0zDhg3j8ccfx2q1Btw6Rq3hPWlrnyfe5vdJTbt27WjXrt0pjystLQVA1z0rn3Rdd2fHI0aM4IknniAnJ4fExEQAVqxYQVRUlMcvWUuU25r5+j1xUUrx+uuvc+ONNxIUFHTKeDIyMtx/VAJNa3hPRowYwV/+8hdsNpt734oVK+jVq1dANj35+j0ZPHgwwcHB7Nixg5EjRwJgs9nYv38/Xbt2rTOejIwMYmNjAy6hgdbxnrS1zxOv81kXZS87evSoio+PV1dccYXKyMhQO3bsUP/3f/+ngoKCVEZGhlLqxFC53/3udyojI0MtX75ctWvXzmOo3Lp161SvXr3UwYMHvVpuW9Rc74nLypUrFaC2bdtW49pvvPGGeuedd9S2bdvUtm3b1BNPPKF0XVevvfZa875oP+fL9yQ/P1+1b99e3XDDDWrr1q1q8eLFKiwsrM0P6W7O92TatGmqU6dO6quvvlLbt29Xt9xyi0pMTFTHjx9XSim1bNkytXDhQrVlyxa1a9cu9dJLL6mwsDD1yCOPtOwPwc/48j2Rz5OmCZikRiml0tPT1e9+9zsVFxenIiMj1fDhw9UXX3zhccz+/fvVRRddpEJDQ1VCQoK6//77lc1mc+//5ptvFKD27dvn1XLbquZ6T5RS6tprr1Vnn312rdd944031BlnnKHCwsJUVFSUGjp0qFq6dKnXX19r5Kv3RCmlfvrpJzVy5EgVHBysOnXqpObOnevV19ZaNdd7UlFRoe6//36VmJioIiMjVVpamtq6dat7/5dffqlSU1NVRESECg8PVwMGDFDz589XDoej2V+zv/PVe1KfckXdNKXa+Ng9IYQQQgQEvx/9JIQQQghRH5LUCCGEECIgSFIjhBBCiIAgSY0QQgghAoIkNUIIIYQICJLUCCGEECIgSFIjhBBCiIAgSY0QQgghAoIkNUIIIYQICJLUCCGEECIgSFIjhBBCiIAgSY0QQgghAsL/A+EfApqBC/wlAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final pop = 121375.0 = 121375.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final pop = 120188.0 = 120188.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final pop = 120594.0 = 120594.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final pop = 121371.0 = 121371.0\n"
     ]
    }
   ],
   "source": [
    "splitVTDlist = [list() for t in range(nHDs)] #each HD's final list of VTDs from a split muni\n",
    "for i,t in enumerate(splitHDlist):\n",
    "    nonSplitUset = set(HDunitList[t]).difference({splitUnitNo[t]})\n",
    "    if 1 == 1: #t in bridgeList: #strategy is to shed noncritical border vtds until pop target met\n",
    "        origSet = set(muniVTDlist[homeU[t]])\n",
    "        for u in HDunitList[t]:\n",
    "            origSet = origSet.union(set(muniVTDlist[u]))\n",
    "        currPop = np.sum([unitPop[u] for u in HDunitList[t] ] )\n",
    "        bridgeU = splitUnitNo[t]\n",
    "        remainingList = muniVTDlist[bridgeU].copy()\n",
    "        sheddableList, shedSet = list(), set()\n",
    "        for v in remainingList:\n",
    "            contig,cContig, _, __ = enclaveCheck(list(origSet.difference(shedSet.union({v}))),vtdNbrs )\n",
    "            if contig and cContig:\n",
    "            #if isContiguous( list(set(remainingList).difference({v}) ), vtdNbrs ):\n",
    "                openNbrSet = set(vtdNbrs[v]) # \"open nbr\" is an adjacent VTD in a non-HD muni\n",
    "                for u in HDunitList[t]:\n",
    "                    openNbrSet = openNbrSet.difference(set(muniVTDlist[u]))\n",
    "                if len(openNbrSet) > 0:\n",
    "                    sheddableList.append(v)\n",
    "                    #print(v,\"is in sheddable List\")\n",
    "            \n",
    "        while currPop > 1.02 * aDP and len(sheddableList) > 0:\n",
    "            shedDist = [ tractCP[v].distance(HDCP[t]) for v in sheddableList ]\n",
    "            shedV = sheddableList[shedDist.index(np.max(shedDist))]\n",
    "            #print(\"I shed vtd\",shedV)\n",
    "            currPop -= tractPop[shedV]\n",
    "            sheddableList.remove(shedV)\n",
    "            remainingList.remove(shedV)\n",
    "            shedSet.add(shedV)\n",
    "            inMuniNbrs = set(vtdNbrs[shedV]).intersection(muniVTDlist[bridgeU]) #newly border-facing vtds\n",
    "            for vv in inMuniNbrs.difference(shedSet.union(set(sheddableList)) ):\n",
    "                contig,cContig, _, __ = enclaveCheck( list( origSet.difference(shedSet.union({vv})) ),vtdNbrs )\n",
    "                if contig and cContig:\n",
    "                #if isContiguous( list(set(remainingList).difference({vv}) ), vtdNbrs ) :\n",
    "                    sheddableList.append(vv)\n",
    "                    #print(vv,\"is now in sheddable List\")\n",
    "        splitVTDlist[t] = set(muniVTDlist[bridgeU]).difference(shedSet)\n",
    "        #print(\"all done trimming HD\",t,\"pop/aDP is now\",r3(currPop/aDP))\n",
    "        if i%20 == 0:\n",
    "            plotPoly(HDCP[t].buffer(0.01))\n",
    "            for u in HDunitList[t]:\n",
    "                plotPoly(unitGeom[u])\n",
    "            for v in splitVTDlist[t]:\n",
    "                plotPoly(tractGeom[v],0.3)\n",
    "                plotCenter(\"in\",tractGeom[v],8)\n",
    "            for v in set(muniVTDlist[bridgeU]).difference(set(splitVTDlist[t])):\n",
    "                plotCenter(v,tractCP[v],8)\n",
    "            plt.show()\n",
    "            print(\"final pop =\",np.sum([unitPop[u] for u in HDunitList[t]]) - np.sum([tractPop[v] for v in shedSet] ) ,\n",
    "                  \"=\",np.sum([unitPop[u] for u in HDunitList[t]]) - unitPop[bridgeU] + np.sum([tractPop[v] for v in splitVTDlist[t]]) )\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "id": "aea7484d-b775-4f1b-b6e6-182c97b22650",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "18515 102009.0 120524.0 120524 133331.0\n"
     ]
    }
   ],
   "source": [
    "SPLITPOP = np.sum([tractPop[v] for v in splitVTDlist[t] ])\n",
    "ORIGPOP = np.sum([unitPop[u] for u in HDunitList[t] ])\n",
    "FULLMUNIPOP = ORIGPOP - unitPop[splitUnitNo[t]]\n",
    "print(SPLITPOP, FULLMUNIPOP, SPLITPOP+FULLMUNIPOP, HDvPop[t],ORIGPOP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "04dd5198-d238-41cc-b57e-a946e3e74adb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "histogram of vtd use\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vtdUse = [0.]*nVTDs\n",
    "finalVTDlist = [list() for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        if splitUnitNo[t] == u:\n",
    "            for v in splitVTDlist[t]:\n",
    "                finalVTDlist[t].append(v)\n",
    "                vtdUse[v] += nDistricts * HDweight[t]\n",
    "        else:\n",
    "            finalVTDlist[t] += muniVTDlist[u]\n",
    "            for v in muniVTDlist[u]:\n",
    "                vtdUse[v] += nDistricts * HDweight[t]\n",
    "popVTDlist = list()\n",
    "for v in range(nVTDs):\n",
    "    if v not in skipList:\n",
    "        popVTDlist.append(v)\n",
    "plt.hist([vtdUse[v] for v in popVTDlist],weights= [tractPop[v] for v in popVTDlist])\n",
    "print(\"histogram of vtd use\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "d98ae9cf-2b88-493b-a4a7-a323c342dfd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "finalHDvPop = [np.sum([tractPop[v] for v in finalVTDlist[t] ]) for t in range(nHDs)]\n",
    "plt.hist([finalHDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP,ls= \"--\")\n",
    "plt.axvline(0.95*aDP, ls=\"dotted\")\n",
    "plt.axvline(1.05*aDP, ls=\"dotted\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "4e9173d8-7247-4cfc-a247-e9bb4a208ea6",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDvPop = finalHDvPop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "59d332e1-2b4b-4e17-90ee-a9c023ee9bde",
   "metadata": {},
   "outputs": [],
   "source": [
    "for t in popHDlist:\n",
    "    if homeU[t] not in HDunitList[t]:\n",
    "        print(t,\"doesn't have home unit\",homeU[t],\"in its unit list. Its split muni no is\",splitUnitNo[t])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "ca4f5b88-ff08-46ce-92d9-f4b71054a5bb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now write the final vtd lists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"now write the final vtd lists to a file\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":finalVTDlist,\n",
    "                      \"centroid x\":HDCPx, \"centroid y\":HDCPy,\"countyNo\":countyNo,\"hasSplitUnit\":hasSplitUnit} )\n",
    "outname = STATE+str(int(nHDs))+\"legislMuniPatchedVTDs.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)  #muni-based complete 11-11-24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c42effd1-7ad5-49f1-b021-536f90ece7c4",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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